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Angelo Oddi

Consiglio Nazionale delle Ricerche (CNR), Institute of Cognitive Sciences and Technologies, Department Member

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Address: Rome, Italy

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University of California, Santa Barbara

Harvard University

David Pierre Leibovitz

Carleton University

Alysson M. Costa

Universidade de São Paulo

University College Cork

University of Cologne

Armando Marques-Guedes

UNL - New University of Lisbon

University of Limerick

Universidad del Norte - Barranquilla, Colombia

Graduate Center of the City University of New York

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Papers by Angelo Oddi

Planning and Scheduling for workflow domains

Multi-Objective Optimization in a Job Shop with Energy Costs through Hybrid Evolutionary Techniques

Proceedings of the International Conference on Automated Planning and Scheduling

Energy costs are an increasingly important issue in real-world scheduling, for both economic and ... more Energy costs are an increasingly important issue in real-world scheduling, for both economic and environmental reasons. This paper deals with a variant of the well-known job shop scheduling problem, where we consider a bi-objective optimization of both the weighted tardiness and the energy costs. To this end, we design a hybrid metaheuristic that combines a genetic algorithm with a novel local search method and a linear programming approach. We also propose an efficient procedure for improving the energy cost of a given schedule. In the experimental study we analyse our proposal and compare it with the state of the art and also with a constraint programming approach, obtaining competitive results.

Autonomous Generation of Symbolic Knowledge via Option Discovery

In this work we present an empirical study where we demonstrate the possibility of developing an ... more In this work we present an empirical study where we demonstrate the possibility of developing an artificial agent that is capable to autonomously explore an experimental scenario. During the exploration, the agent is able to discover and learn interesting options allowing to interact with the environment without any assigned task, and then abstract and re-use the acquired knowledge to solve the assigned tasks. We test the system in the so-called Treasure Game domain described in the recent literature and we empirically demonstrate that the discovered options can be abstracted in an probabilistic symbolic planning model (using the PPDDL language), which allowed the agent to generate symbolic plans to achieve extrinsic goals.

Learning High-Level Planning Symbols from Intrinsically Motivated Experience

One of the main challenges in Artificial Intelligence is the problem of abstracting high-level mo... more One of the main challenges in Artificial Intelligence is the problem of abstracting high-level models directly leveraging the interaction between the agent and the environment, where such interaction is typically performed at low-level through the agent's sensing and actuating capabilities. Such information abstraction process indeed reveals invaluable for high-level planning, as it allows to make explicit the causal relations existing at the high-level which would otherwise remain hidden at low-level. In this respect, some interesting work has been done in the recent literature. For instance, in [3] an algorithm is presented for automatically producing symbolic domains based on the Planning Domain Definition Language (PDDL, see [2]), starting from a set of low-level skills represented in the form of abstract subgoal options. The contribution of this work is the following. First, we extend the scope of the information abstraction procedure proposed in [3] by directly linking it ...

An Intrinsically Motivated Planning Architecture for Curiosity-driven Robots

plans to continuous actions into the real working domain, is well recognised in the literature [1... more plans to continuous actions into the real working domain, is well recognised in the literature [1, 4, 6]. However, we have also inserted at the same layer the subsystem (called “KoPro+”, see [8]) for the automatic translation of the newly acquired skills, from a low-level sub-symbolic representation (generated by “GRAIL-IM-Learning”) to a high-level symbolic representation. In some sense, the “KoPro+” module has a dual role in comparison to the Executor; in fact, the learning process can be seen as opposite to the execution process, as it maps low-level sub-symbolic representation into abstract symbolic representation. 3 Operational Evaluation The validation and verification of the IMPACT framework was carried out in the form of two demonstration test cases. The Rover scenario, which demonstrates how the IMPACT system can discover new ways to reach an already known effect by applying the procedure (called KoPro+, see [8]) for the automatic translation of the newly acquired skills fr...

Surveying the Versatility of Constraint-Based Large Neighborhood Search for Scheduling Problems

Communications in Computer and Information Science, 2015

Constraint-based search techniques have gained increasing attention in recent years as a basis fo... more Constraint-based search techniques have gained increasing attention in recent years as a basis for scheduling procedures that are capable of accommodating a wide range of constraints. Among these, the Large Neighborhood Search (lns) has largely proven to be a very effective heuristic-based methodology. Its basic optimization cycle consists of a continuous iteration of two steps where the solution is first relaxed and then re-constructed. In Constraint Programming terms, relaxing entails the retraction of some previously imposed constraints, while re-constructing entails imposing new constraints, searching for a better solution. Each iteration of constraint removal and re-insertion can be considered as the examination of a large neighborhood move, hence the procedure’s name. Over the years, LNS has been successfully employed over a wide range of different problems; this paper intends to provide an overview of some utilization examples that demonstrate both the versatility and the effectiveness of the procedure against significantly difficult scheduling benchmarks known in literature.

A formal domain description language for a temporal planner

Lecture Notes in Computer Science, 1995

The Domain Description Language (DDL) is the basic knowledge representation service in any proble... more The Domain Description Language (DDL) is the basic knowledge representation service in any problem solving architecture. This paper introduces DDL.1 a DDL for a planning and scheduling architecture that adopts basic features from control theory and extends them to the specification of constraints. A general overview of the language is given, its syntax and semantics described. Finally, the problem of temporal planning by using such a language is briefly addressed.

Planning with Concurrency, Time and Resources

Intelligent Techniques for Planning

This chapter proposes to model a planning problem (e.g., the control of a satellite system) by id... more This chapter proposes to model a planning problem (e.g., the control of a satellite system) by identifying a set of relevant components in the domain (e.g., communication channels, on-board memory or batteries), which need to be controlled to obtain a desired temporal behavior. The domain model is enriched with the description of relevant constraints with respect to possible concurrency, temporal limits and scarce resource availability. The paper proposes a planning framework based on this view that relies on a formalization of the problem as a Constraint Satisfaction Problem (CSP) and defines an algorithmic template in which the integration of planning and scheduling is a fundamental feature. In addition, the paper describes the current implementation of a constraint-based planner called OMP that is grounded on these ideas and shows the role constraints have in this planner, both at domain description level and as a guide for problem solving.

Scatter search with path relinking for the job shop with time lags and setup times

Computers & Operations Research, 2015

This paper addresses the job shop scheduling problem with time lags and sequence-dependent setup ... more This paper addresses the job shop scheduling problem with time lags and sequence-dependent setup times. This is an extension of the job shop scheduling problem with many applications in real production environments. We propose a scatter search algorithm which uses path relinking and tabu search in its core. We consider both feasible and unfeasible schedules in the execution, and we propose effective neighborhood structures with the objectives of reducing the makespan and regain feasibility. We also define new procedures for estimating the quality of the neighbors. We conducted an experimental study to compare the proposed algorithm with the state-of-the-art, in benchmarks both with and without setups. In this study, our algorithm has obtained very competitive results in a reduced run time.

Iterative Flattening Search on RCPSP/max Problems: Recent Developments

Lecture Notes in Computer Science, 2009

This paper proposes an iterative improvement algorithm for solving instances of the Resource Cons... more This paper proposes an iterative improvement algorithm for solving instances of the Resource Constraint Project Scheduling Problem with Time-Windows (RCPSP/max). The algorithm is based on Iterative Flattening Search (ifs), an effective meta-heuristic strategy proposed over the past years for solving multi-capacity optimization scheduling problems. Given an initial solution, ifs iteratively applies two steps: (1) a subset of solving decisions are randomly retracted from a current solution (relaxation-step); (2) a new solution is incrementally recomputed (flattening-step). At the end, the best solution found is returned. To the best of our knowledge this is the first paper which proposes a version of ifs for solving RCPSP/max instances. The main contribution of this paper is threefold: (1) we succeed in improving 15 out of 90 solutions with respect to the officially published current best, thus demonstrating the general efficacy of ifs; (2) we highlight an intrisic limitation of the original ifs strategy in solving RCPSP/max, such that under certain circumstances the two-step improvement loop can get stuck in a status where no solving decision can be retracted; (3) we propose two different escaping strategies which extend the original ifs procedure. An experimental evaluation ends the paper, comparing the performances of the proposed escaping strategies against the original ifs procedure.

Maintaining consistency in a Quantitative Time Manager

Proceedings of 1993 IEEE Conference on Tools with Al (TAI-93)

ABSTRACT

An Empirical Experience with 3DROV Simulator: Testing an Advanced Autonomous Controller for Rover Operations

The aim of this paper is to convey our experience using the ESA's 3DROV planetary rover simulator... more The aim of this paper is to convey our experience using the ESA's 3DROV planetary rover simulator as a visualization and validation tool through a dynamic analysis on the performance of an advanced autonomous control architecture: a power-aware, model-based control system with applications in rover-based mission operations which integrates advanced constraint-based reasoning within a flexible control execution management process. The analysis focuses on the validation of the main capabilities of the control system through three representative simulation examples executed upon an integrated testbed platform with 3DROV. More concretely, the target of the simulation tests is twofold: (i) to demonstrate the main capabilities of the controller; and (ii) to evaluate its performance on overcoming specific anomalous situations which might threaten the whole mission execution success.

MrSPOCK-STEPS IN DEVELOPING AN END-TO-END SPACE APPLICATION

Computational Intelligence, 2011

This article elaborates around a recent effort to build a planning system that helps human missio... more This article elaborates around a recent effort to build a planning system that helps human mission planning in a space mission. Specifically, the article describes the steps that brought us to develop MrSPOCK, the MARS EXPRESS Science Plan Opportunities Coordination Kit, a tool for supporting long-term planning in the MARS EXPRESS mission of the European Space Agency. In showing our effort for creating MrSPOCK, we will underscore the key ingredients for developing complete applications and how they are connected to a stable line of research on planning and scheduling with timelines.

Iterative-sampling search for job shop scheduling with setup times

This paper presents a heuristic algorithm for solving the job-shop scheduling problem with sequen... more This paper presents a heuristic algorithm for solving the job-shop scheduling problem with sequence dependent setup times (SDST-JSSP). The algorithm relies on a core constraint-based search procedure, which generates consistent ordering of activities requiring the same resource by incrementally imposing precedence constraints on a temporal feasible solution. Key to the effectiveness of the search procedure is a conflict sampling method biased toward selection of most critical conflict and coupled with a non-deterministic choice heuristic to guide the base conflict resolution process. This constraint-based search is then embedded within a larger iterative-sampling search framework to broaden search space coverage and promote solution optimization. The efficacy of the overall heuristic algorithm is demonstrated empirically on a set of previously studied job-shop scheduling benchmark problems with sequence dependent setup times.

MrSPOCK: Generating a planning system through a timeline representation framework

This paper describes aspects of a project, named APSI (Advanced Planning and Scheduling Initiativ... more This paper describes aspects of a project, named APSI (Advanced Planning and Scheduling Initiative), aiming at creating a general, flexible and reusable software architecture to address planning problems in space missions. It introduces our recent work that realized a general software framework for supporting development of planning and scheduling applications for space. The framework which is named Trf (Timeline-based Representation Framework) aims at supporting application development within different ESA missions and is currently being tested on three problem examples all solved on top of the Trf functionalities. The paper describes the Trf three-layerd software architecture and shows how it has been used to deploy a complete application named MrSPOCK an interactive system for Mars Express Long Term Planning.

Developing an end-to-end planning application from a timeline representation framework

This paper describes aspects of a project aiming at creating a general, flexible and reusable sof... more This paper describes aspects of a project aiming at creating a general, flexible and reusable software architecture to address planning problems in space missions. It introduces recent work to realize an open software framework for supporting development of planning and scheduling space applications. The framework, which is named TRF (Timeline-based Representation Framework), aims at supporting application development within different space missions for the European Space Agency (ESA). It is currently being tested on three problem examples, all solved on top of the TRF functionalities. This paper describes the TRF three-layered software architecture and shows how it has been used to deploy a complete application, named MrSPOCK, an interactive system for Long Term Planning in the MARS EXPRESS operational mission.

MrSPOCK: A long-term planning tool for MARS EXPRESS

IWPSS-09. 6th International …, 2009

This paper describes MrSPOCK (MARS EXPRESS Science Plan Opportunities Coordination Kit), a decisi... more This paper describes MrSPOCK (MARS EXPRESS Science Plan Opportunities Coordination Kit), a decision support system for long-term mission planning. The work was carried out within the Advanced Planning and Scheduling Initiative (APSI), a project funded by ESA which aims at creating the basis for a general, flexible and reusable software framework (named here APSI-TRF-APSI Timeline-based Representation Framework) to facilitate injection of AI Planning and Scheduling in space missions to enhance ESA mission operation management performance. The paper first overviews the framework features then shows them at work in supporting the realization of MrSPOCK. The paper shows how to solve an interesting multi-objective optimization problem requiring the satisfaction of various temporal and causal constraints. It then shows how the modeling capabilities of the APSI-TRF supports both the synthesis of an end-to-end approach to the problem, and open the possibility to flexible extensions of the application with added value in terms of modularity, extensibility and reusability. To this purpose, the main steps for the development of an extended application, which includes a model of the satellite power management subsystem are also described.

O-OScAR: A flexible object-oriented architecture for schedule management in space applications

Artificial Intelligence, Robotics and …, 1999

... A quite coml)lex example of the new range of functionalities given by MCM 0-OSCAR is repiesen... more

APSI Case# 1: Pre-planning Science Operations in Mars Express

Proc. of iSAIRAS-08, 2008

This paper gives a preliminary overview on an ongoing effort to build a planning system to suppor... more This paper gives a preliminary overview on an ongoing effort to build a planning system to support ESA mission planners in Long Term Planning for Mars Express. The output of the tool is a pre-optimized skeleton plan of the communication windows and spacecraft maintenance slots, that is used as a support in the dialogue between science and operation team in early pre-planning of activities. To capture details of the domain we have specialized the OMPS planning architecture to obtain a rapid prototyping tool that can ...

Planning Science Data Return of Mars Express with Support of Artificial Intelligence

SpaceOps 2006 Conference, 2006

Mars Express (MEX) has been in orbit around Mars since the beginning of 2004. A complex science p... more Mars Express (MEX) has been in orbit around Mars since the beginning of 2004. A complex science payload, including a camera, spectrometers, a particle detector, a radar and a transponder for communications with Mars landers, generates a large amount of science data that need to be transferred to the ground. For MEX, a dedicated ESA ground station and a number of DSN stations are available to receive the data. As the mission is operated in a store and forward-type manner, all data are stored on board before it is down-linked. Depending on the season, the downlink data rate varies between 28 kbps and 182 kbps. The generation of science data has to take into account: a) the downlink bit rate b) the available downlink windows and c) the available mass memory space on the spacecraft. The amount of data to be down-linked varies between 800 Mbit and more than 5 Gbit per day. The allocation of downlink windows is driven largely by the science requirements and changes from orbit to orbit, i.e. there are no dedicated data downlink slots allocated as a fixed daily pattern, downlink slots continuously vary in length and time of day. Data have to be dumped from the onboard mass memory before more data are written into it to avoid loss of data. Consequently, the generation of a data downlink plan has been a challenge since the start of the mission. It became obvious that a dedicated tool was needed to help resolve the conflicting requirements. An operational software system was produced, based on experience gained from early MEX operations, and on an ESA study, referred to as MEXAR (Mars Express Scheduling Architecture), that led to a prototype of a software system demonstrating that artificial intelligence techniques for planning and scheduling can be beneficially applied to a real space mission. The tool has been successfully deployed in the MEX mission planning process as part of a suite of tools to support planning. Major objectives of the tool are the automation of the data dumping planning process and the maximization of the amount of dumped data. The paper describes the operational requirements for a data dumping tool, its iterative implementation process up to the final product and the operational assessment in terms of reduction of manpower effort and increase in the volume of dumped data.

Planning and Scheduling for workflow domains

Multi-Objective Optimization in a Job Shop with Energy Costs through Hybrid Evolutionary Techniques

Proceedings of the International Conference on Automated Planning and Scheduling

Energy costs are an increasingly important issue in real-world scheduling, for both economic and ... more Energy costs are an increasingly important issue in real-world scheduling, for both economic and environmental reasons. This paper deals with a variant of the well-known job shop scheduling problem, where we consider a bi-objective optimization of both the weighted tardiness and the energy costs. To this end, we design a hybrid metaheuristic that combines a genetic algorithm with a novel local search method and a linear programming approach. We also propose an efficient procedure for improving the energy cost of a given schedule. In the experimental study we analyse our proposal and compare it with the state of the art and also with a constraint programming approach, obtaining competitive results.

Autonomous Generation of Symbolic Knowledge via Option Discovery

In this work we present an empirical study where we demonstrate the possibility of developing an ... more In this work we present an empirical study where we demonstrate the possibility of developing an artificial agent that is capable to autonomously explore an experimental scenario. During the exploration, the agent is able to discover and learn interesting options allowing to interact with the environment without any assigned task, and then abstract and re-use the acquired knowledge to solve the assigned tasks. We test the system in the so-called Treasure Game domain described in the recent literature and we empirically demonstrate that the discovered options can be abstracted in an probabilistic symbolic planning model (using the PPDDL language), which allowed the agent to generate symbolic plans to achieve extrinsic goals.

Learning High-Level Planning Symbols from Intrinsically Motivated Experience

One of the main challenges in Artificial Intelligence is the problem of abstracting high-level mo... more One of the main challenges in Artificial Intelligence is the problem of abstracting high-level models directly leveraging the interaction between the agent and the environment, where such interaction is typically performed at low-level through the agent's sensing and actuating capabilities. Such information abstraction process indeed reveals invaluable for high-level planning, as it allows to make explicit the causal relations existing at the high-level which would otherwise remain hidden at low-level. In this respect, some interesting work has been done in the recent literature. For instance, in [3] an algorithm is presented for automatically producing symbolic domains based on the Planning Domain Definition Language (PDDL, see [2]), starting from a set of low-level skills represented in the form of abstract subgoal options. The contribution of this work is the following. First, we extend the scope of the information abstraction procedure proposed in [3] by directly linking it ...

An Intrinsically Motivated Planning Architecture for Curiosity-driven Robots

plans to continuous actions into the real working domain, is well recognised in the literature [1... more plans to continuous actions into the real working domain, is well recognised in the literature [1, 4, 6]. However, we have also inserted at the same layer the subsystem (called “KoPro+”, see [8]) for the automatic translation of the newly acquired skills, from a low-level sub-symbolic representation (generated by “GRAIL-IM-Learning”) to a high-level symbolic representation. In some sense, the “KoPro+” module has a dual role in comparison to the Executor; in fact, the learning process can be seen as opposite to the execution process, as it maps low-level sub-symbolic representation into abstract symbolic representation. 3 Operational Evaluation The validation and verification of the IMPACT framework was carried out in the form of two demonstration test cases. The Rover scenario, which demonstrates how the IMPACT system can discover new ways to reach an already known effect by applying the procedure (called KoPro+, see [8]) for the automatic translation of the newly acquired skills fr...

Surveying the Versatility of Constraint-Based Large Neighborhood Search for Scheduling Problems

Communications in Computer and Information Science, 2015

Constraint-based search techniques have gained increasing attention in recent years as a basis fo... more Constraint-based search techniques have gained increasing attention in recent years as a basis for scheduling procedures that are capable of accommodating a wide range of constraints. Among these, the Large Neighborhood Search (lns) has largely proven to be a very effective heuristic-based methodology. Its basic optimization cycle consists of a continuous iteration of two steps where the solution is first relaxed and then re-constructed. In Constraint Programming terms, relaxing entails the retraction of some previously imposed constraints, while re-constructing entails imposing new constraints, searching for a better solution. Each iteration of constraint removal and re-insertion can be considered as the examination of a large neighborhood move, hence the procedure’s name. Over the years, LNS has been successfully employed over a wide range of different problems; this paper intends to provide an overview of some utilization examples that demonstrate both the versatility and the effectiveness of the procedure against significantly difficult scheduling benchmarks known in literature.

A formal domain description language for a temporal planner

Lecture Notes in Computer Science, 1995

The Domain Description Language (DDL) is the basic knowledge representation service in any proble... more The Domain Description Language (DDL) is the basic knowledge representation service in any problem solving architecture. This paper introduces DDL.1 a DDL for a planning and scheduling architecture that adopts basic features from control theory and extends them to the specification of constraints. A general overview of the language is given, its syntax and semantics described. Finally, the problem of temporal planning by using such a language is briefly addressed.

Planning with Concurrency, Time and Resources

Intelligent Techniques for Planning

This chapter proposes to model a planning problem (e.g., the control of a satellite system) by id... more This chapter proposes to model a planning problem (e.g., the control of a satellite system) by identifying a set of relevant components in the domain (e.g., communication channels, on-board memory or batteries), which need to be controlled to obtain a desired temporal behavior. The domain model is enriched with the description of relevant constraints with respect to possible concurrency, temporal limits and scarce resource availability. The paper proposes a planning framework based on this view that relies on a formalization of the problem as a Constraint Satisfaction Problem (CSP) and defines an algorithmic template in which the integration of planning and scheduling is a fundamental feature. In addition, the paper describes the current implementation of a constraint-based planner called OMP that is grounded on these ideas and shows the role constraints have in this planner, both at domain description level and as a guide for problem solving.

Scatter search with path relinking for the job shop with time lags and setup times

Computers & Operations Research, 2015

This paper addresses the job shop scheduling problem with time lags and sequence-dependent setup ... more This paper addresses the job shop scheduling problem with time lags and sequence-dependent setup times. This is an extension of the job shop scheduling problem with many applications in real production environments. We propose a scatter search algorithm which uses path relinking and tabu search in its core. We consider both feasible and unfeasible schedules in the execution, and we propose effective neighborhood structures with the objectives of reducing the makespan and regain feasibility. We also define new procedures for estimating the quality of the neighbors. We conducted an experimental study to compare the proposed algorithm with the state-of-the-art, in benchmarks both with and without setups. In this study, our algorithm has obtained very competitive results in a reduced run time.

Iterative Flattening Search on RCPSP/max Problems: Recent Developments

Lecture Notes in Computer Science, 2009

This paper proposes an iterative improvement algorithm for solving instances of the Resource Cons... more This paper proposes an iterative improvement algorithm for solving instances of the Resource Constraint Project Scheduling Problem with Time-Windows (RCPSP/max). The algorithm is based on Iterative Flattening Search (ifs), an effective meta-heuristic strategy proposed over the past years for solving multi-capacity optimization scheduling problems. Given an initial solution, ifs iteratively applies two steps: (1) a subset of solving decisions are randomly retracted from a current solution (relaxation-step); (2) a new solution is incrementally recomputed (flattening-step). At the end, the best solution found is returned. To the best of our knowledge this is the first paper which proposes a version of ifs for solving RCPSP/max instances. The main contribution of this paper is threefold: (1) we succeed in improving 15 out of 90 solutions with respect to the officially published current best, thus demonstrating the general efficacy of ifs; (2) we highlight an intrisic limitation of the original ifs strategy in solving RCPSP/max, such that under certain circumstances the two-step improvement loop can get stuck in a status where no solving decision can be retracted; (3) we propose two different escaping strategies which extend the original ifs procedure. An experimental evaluation ends the paper, comparing the performances of the proposed escaping strategies against the original ifs procedure.

Maintaining consistency in a Quantitative Time Manager

Proceedings of 1993 IEEE Conference on Tools with Al (TAI-93)

ABSTRACT

An Empirical Experience with 3DROV Simulator: Testing an Advanced Autonomous Controller for Rover Operations

The aim of this paper is to convey our experience using the ESA's 3DROV planetary rover simulator... more The aim of this paper is to convey our experience using the ESA's 3DROV planetary rover simulator as a visualization and validation tool through a dynamic analysis on the performance of an advanced autonomous control architecture: a power-aware, model-based control system with applications in rover-based mission operations which integrates advanced constraint-based reasoning within a flexible control execution management process. The analysis focuses on the validation of the main capabilities of the control system through three representative simulation examples executed upon an integrated testbed platform with 3DROV. More concretely, the target of the simulation tests is twofold: (i) to demonstrate the main capabilities of the controller; and (ii) to evaluate its performance on overcoming specific anomalous situations which might threaten the whole mission execution success.

MrSPOCK-STEPS IN DEVELOPING AN END-TO-END SPACE APPLICATION

Computational Intelligence, 2011

This article elaborates around a recent effort to build a planning system that helps human missio... more This article elaborates around a recent effort to build a planning system that helps human mission planning in a space mission. Specifically, the article describes the steps that brought us to develop MrSPOCK, the MARS EXPRESS Science Plan Opportunities Coordination Kit, a tool for supporting long-term planning in the MARS EXPRESS mission of the European Space Agency. In showing our effort for creating MrSPOCK, we will underscore the key ingredients for developing complete applications and how they are connected to a stable line of research on planning and scheduling with timelines.

Iterative-sampling search for job shop scheduling with setup times

This paper presents a heuristic algorithm for solving the job-shop scheduling problem with sequen... more This paper presents a heuristic algorithm for solving the job-shop scheduling problem with sequence dependent setup times (SDST-JSSP). The algorithm relies on a core constraint-based search procedure, which generates consistent ordering of activities requiring the same resource by incrementally imposing precedence constraints on a temporal feasible solution. Key to the effectiveness of the search procedure is a conflict sampling method biased toward selection of most critical conflict and coupled with a non-deterministic choice heuristic to guide the base conflict resolution process. This constraint-based search is then embedded within a larger iterative-sampling search framework to broaden search space coverage and promote solution optimization. The efficacy of the overall heuristic algorithm is demonstrated empirically on a set of previously studied job-shop scheduling benchmark problems with sequence dependent setup times.

MrSPOCK: Generating a planning system through a timeline representation framework

This paper describes aspects of a project, named APSI (Advanced Planning and Scheduling Initiativ... more This paper describes aspects of a project, named APSI (Advanced Planning and Scheduling Initiative), aiming at creating a general, flexible and reusable software architecture to address planning problems in space missions. It introduces our recent work that realized a general software framework for supporting development of planning and scheduling applications for space. The framework which is named Trf (Timeline-based Representation Framework) aims at supporting application development within different ESA missions and is currently being tested on three problem examples all solved on top of the Trf functionalities. The paper describes the Trf three-layerd software architecture and shows how it has been used to deploy a complete application named MrSPOCK an interactive system for Mars Express Long Term Planning.

Developing an end-to-end planning application from a timeline representation framework

This paper describes aspects of a project aiming at creating a general, flexible and reusable sof... more This paper describes aspects of a project aiming at creating a general, flexible and reusable software architecture to address planning problems in space missions. It introduces recent work to realize an open software framework for supporting development of planning and scheduling space applications. The framework, which is named TRF (Timeline-based Representation Framework), aims at supporting application development within different space missions for the European Space Agency (ESA). It is currently being tested on three problem examples, all solved on top of the TRF functionalities. This paper describes the TRF three-layered software architecture and shows how it has been used to deploy a complete application, named MrSPOCK, an interactive system for Long Term Planning in the MARS EXPRESS operational mission.

MrSPOCK: A long-term planning tool for MARS EXPRESS

IWPSS-09. 6th International …, 2009

This paper describes MrSPOCK (MARS EXPRESS Science Plan Opportunities Coordination Kit), a decisi... more This paper describes MrSPOCK (MARS EXPRESS Science Plan Opportunities Coordination Kit), a decision support system for long-term mission planning. The work was carried out within the Advanced Planning and Scheduling Initiative (APSI), a project funded by ESA which aims at creating the basis for a general, flexible and reusable software framework (named here APSI-TRF-APSI Timeline-based Representation Framework) to facilitate injection of AI Planning and Scheduling in space missions to enhance ESA mission operation management performance. The paper first overviews the framework features then shows them at work in supporting the realization of MrSPOCK. The paper shows how to solve an interesting multi-objective optimization problem requiring the satisfaction of various temporal and causal constraints. It then shows how the modeling capabilities of the APSI-TRF supports both the synthesis of an end-to-end approach to the problem, and open the possibility to flexible extensions of the application with added value in terms of modularity, extensibility and reusability. To this purpose, the main steps for the development of an extended application, which includes a model of the satellite power management subsystem are also described.

O-OScAR: A flexible object-oriented architecture for schedule management in space applications

Artificial Intelligence, Robotics and …, 1999

... A quite coml)lex example of the new range of functionalities given by MCM 0-OSCAR is repiesen... more

APSI Case# 1: Pre-planning Science Operations in Mars Express

Proc. of iSAIRAS-08, 2008

This paper gives a preliminary overview on an ongoing effort to build a planning system to suppor... more This paper gives a preliminary overview on an ongoing effort to build a planning system to support ESA mission planners in Long Term Planning for Mars Express. The output of the tool is a pre-optimized skeleton plan of the communication windows and spacecraft maintenance slots, that is used as a support in the dialogue between science and operation team in early pre-planning of activities. To capture details of the domain we have specialized the OMPS planning architecture to obtain a rapid prototyping tool that can ...

Planning Science Data Return of Mars Express with Support of Artificial Intelligence

SpaceOps 2006 Conference, 2006

Mars Express (MEX) has been in orbit around Mars since the beginning of 2004. A complex science p... more Mars Express (MEX) has been in orbit around Mars since the beginning of 2004. A complex science payload, including a camera, spectrometers, a particle detector, a radar and a transponder for communications with Mars landers, generates a large amount of science data that need to be transferred to the ground. For MEX, a dedicated ESA ground station and a number of DSN stations are available to receive the data. As the mission is operated in a store and forward-type manner, all data are stored on board before it is down-linked. Depending on the season, the downlink data rate varies between 28 kbps and 182 kbps. The generation of science data has to take into account: a) the downlink bit rate b) the available downlink windows and c) the available mass memory space on the spacecraft. The amount of data to be down-linked varies between 800 Mbit and more than 5 Gbit per day. The allocation of downlink windows is driven largely by the science requirements and changes from orbit to orbit, i.e. there are no dedicated data downlink slots allocated as a fixed daily pattern, downlink slots continuously vary in length and time of day. Data have to be dumped from the onboard mass memory before more data are written into it to avoid loss of data. Consequently, the generation of a data downlink plan has been a challenge since the start of the mission. It became obvious that a dedicated tool was needed to help resolve the conflicting requirements. An operational software system was produced, based on experience gained from early MEX operations, and on an ESA study, referred to as MEXAR (Mars Express Scheduling Architecture), that led to a prototype of a software system demonstrating that artificial intelligence techniques for planning and scheduling can be beneficially applied to a real space mission. The tool has been successfully deployed in the MEX mission planning process as part of a suite of tools to support planning. Major objectives of the tool are the automation of the data dumping planning process and the maximization of the amount of dumped data. The paper describes the operational requirements for a data dumping tool, its iterative implementation process up to the final product and the operational assessment in terms of reduction of manpower effort and increase in the volume of dumped data.