This paper presents HyFlex, a software framework for the development of cross-domain search metho... more This paper presents HyFlex, a software framework for the development of cross-domain search methodologies. The framework features a common software interface for dealing with different combinatorial optimisation problems and provides the algorithm components that are problem specific. In this way, the algorithm designer does not require a detailed knowledge of the problem domains and thus can concentrate his/her efforts on designing adaptive general-purpose optimisation algorithms. Six hard combinatorial problems are fully implemented: maximum satisfiability, one dimensional bin packing, permutation flow shop, personnel scheduling, traveling salesman and vehicle routing. Each domain contains a varied set of instances, including real-world industrial data and an extensive set of state-of-the-art problem specific heuristics and search operators. HyFlex represents a valuable new benchmark of heuristic search generality, with which adaptive cross-domain algorithms are being easily developed and reliably compared.This article serves both as a tutorial and a as survey of the research achievements and publications so far using HyFlex.
We present a hybrid approach of goal programming and meta-heuristic search to find compromise sol... more We present a hybrid approach of goal programming and meta-heuristic search to find compromise solutions for a difficult employee scheduling problem, i.e. nurse rostering with many hard and soft constraints. By employing a goal programming model with different parameter settings in its objective function, we can easily obtain a coarse solution where only the system constraints (i.e. hard constraints) are satisfied and an ideal objective-value vector where each single goal (i.e. each soft constraint) reaches its optimal value. The coarse solution is generally unusable in practise, but it can act as an initial point for the subsequent meta-heuristic search to speed up the convergence. Also, the ideal objective-value vector is, of course, usually unachievable, but it can help a multi-criteria search method (i.e. compromise programming) to evaluate the fitness of obtained solutions more efficiently. By incorporating three distance metrics with changing weight vectors, we propose a new time-predefined meta-heuristic approach, which we call the falling tide algorithm, and apply it under a multi-objective framework to find various compromise solutions. By this approach, not only can we achieve a trade off between the computational time and the solution quality, but also we can achieve a trade off between the conflicting objectives to enable better decision-making.
In an attempt to ensure good-quality printouts of our technical reports, from the supplied PDF fi... more In an attempt to ensure good-quality printouts of our technical reports, from the supplied PDF files, we process to PDF using Acrobat Distiller. We encourage our authors to use outline fonts coupled with embedding of the used subset of all fonts (in either Truetype or Type 1 formats) except for the standard Acrobat typeface families of Times, Helvetica (Arial), Courier and Symbol. In the case of papers prepared using TEX or LATEX we endeavour to use subsetted Type 1 fonts, supplied by Y&Y Inc., for the Computer Modern, Lucida Bright and Mathtime families, rather than the public-domain Computer Modern bitmapped fonts. Note that the Y&Y font subsets are embedded under a site license issued by Y&Y Inc.
To the extent reasonable and practicable the material made available in Nottingham ePrints has be... more To the extent reasonable and practicable the material made available in Nottingham ePrints has been checked for eligibility before being made available.
To the extent reasonable and practicable the material made available in Nottingham ePrints has be... more To the extent reasonable and practicable the material made available in Nottingham ePrints has been checked for eligibility before being made available.
International Journal of Production Economics, 2016
Increasing energy price and requirements to reduce emission are new challenges faced by manufactu... more Increasing energy price and requirements to reduce emission are new challenges faced by manufacturing enterprises. A considerable amount of energy is wasted by machines due to their underutilisation. Consequently, energy saving can be achieved by turning off the machines when they lay idle for a comparatively long period. Otherwise, turning the machine off and back on will consume more energy than leave it stay idle. Thus, an effective way to reduce energy consumption at the system level is by employing intelligent scheduling techniques which are capable of integrating fragmented short idle periods on the machines into large ones. Such scheduling will create opportunities for switching off underutilised resources while at the same time maintaining the production performance. This paper introduces a model for the bi-objective optimisation problem that minimises the total non-processing electricity consumption and total weighted tardiness in a job shop. The Turn off/Turn on is applied as one of the electricity saving approaches. A novel multi-objective genetic algorithm based on NSGA-II is developed. Two new steps are introduced for the purpose of expanding the solution pool and then selecting the elite solutions. The research presented in this paper is focused on the classical job shop environment, which is widely used in the manufacturing industry and provides considerable opportunities for energy saving. The algorithm is validated on job shop problem instances to show its effectiveness.
Radiotherapy treatment planning aims at delivering a sufficient radiation dose to cancerous tumou... more Radiotherapy treatment planning aims at delivering a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour-surrounding area. It is a time-consuming trial-and-error process that requires the expertise of a group of medical experts including oncologists and medical physicists and can take from 2 to 3h to a few days. Our objective is to improve the performance of our previously built case-based reasoning (CBR) system for brain tumour radiotherapy treatment planning. In this system, a treatment plan for a new patient is retrieved from a case base containing patient cases treated in the past and their treatment plans. However, this system does not perform any adaptation, which is needed to account for any difference between the new and retrieved cases. Generally, the adaptation phase is considered to be intrinsically knowledge-intensive and domain-dependent. Therefore, an adaptation often requires a large amount of domain-specific knowledge, which...
Many manufacturing companies in China currently are suffering from a Rolling Blackout policy for ... more Many manufacturing companies in China currently are suffering from a Rolling Blackout policy for the industry electricity supply which means that the government electricity is cut off several days in every week resulting in manufacturing companies illegally starting their own diesel generators to maintain production. However, the private generation of electricity is more polluting and costly than the government supplied resource. if they do not have access to multi-objective optimisation tools. The Non-dominant Sorting Genetic Algorithm has been used as the basis for solving the optimisation problem. Case studies based on four modified job shop instances have been studied to show the effectiveness of the proposed heuristic and the algorithm.
Ant colony optimisation, a constructive metaheuristic inspired by the foraging behaviour of ants,... more Ant colony optimisation, a constructive metaheuristic inspired by the foraging behaviour of ants, has been applied to a wide range of problems since its inception. Many of these are production scheduling problems such as the job shop, in which a collection of operations (grouped into jobs) must be scheduled for processing on different machines. In typical ACO applications, solutions are generated by constructing a permutation of the operations, from which a deterministic algorithm can generate the actual schedule. This paper considers an alternative approach in which each machine is assigned one of a number of alternative dispatching rules, which heuristically determines the processing order for that machine. This representation creates a substantially smaller search space that likely contains good solutions. The performance of both approaches is compared on a real-world job shop scheduling problem in which processing times and job due dates are modelled with fuzzy sets. Results indicate that the new approach produces better solutions more quickly than the traditional approach.
2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422)
This paper describes a new model for robust predictive/reactive scheduling of steel continuous ca... more This paper describes a new model for robust predictive/reactive scheduling of steel continuous casting based on the use of multi-agents, tabu search and heuristic approaches. A continuous caster agent generates a predictive production schedule taking into account manufacturing requirements and local constraints using tabu search. The predictive schedule is modified so as to minimise deviation between the performance measure values of the realised and predictive schedules in order to react to real-time events. We propose several schedule-repair and complete reschedule strategies to handle the real-time events, evaluate and compare their performance. The decision as to whether to locally repair the schedule or reschedule from scratch (complete reschedule) is based on three measures: robustness, utility and stability. Utility measures the change in schedule objective following schedule revision. Stability measures the deviation from the original schedule caused by schedule revision to quantify the undesirability of making large changes to the initial predictive schedule unless absolutely necessary. Robustness combines the utility and stability measures. In order to investigate the performance of these measures and strategies, simulation experiments were carried out and results are reported.
Steel production is a complex process and finding coherent and effective schedules for the wide v... more Steel production is a complex process and finding coherent and effective schedules for the wide variety of production steps, in a dynamic environment, is a challenging task. In this paper we propose a multi-agent architecture for integrated dynamic scheduling of the hot strip mill and the continuous caster. The scheduling systems of these processes have very different objectives and constraints, and operate in an environment where there is a substantial quantity of real-time information concerning production failures and customer requests. Each process is assigned to an agent which independently, seeks an optimal dynamic schedule at a local level taking into account local objectives, real-time information and information received from other agents. Each agent can react to real-time events in order to fix any problems that occur. We focus here, particularly, on the hot strip mill agent which uses a tabu search heuristic to create good predictive-reactive schedules quickly. The other agents simulate the production of the coil orders and the real-time events, which occur during the scheduling process. When real-time events occur on the hot strip mill, the hot strip mill agent might decide whether to repair the current schedule or reschedule from scratch. To address this problem, a range of schedule repair and complete rescheduling strategies are investigated and their performance is assessed with respect to measures of utility, stability and robustness, using an experimental simulation framework.
This paper presents a fuzzy approach to capacitated flow shop scheduling problem. Fuzzy sets are ... more This paper presents a fuzzy approach to capacitated flow shop scheduling problem. Fuzzy sets are applied to express the flexible constraints on capacity of each period in the scheduling horizon. Fuzzy sets are also used to model the processing times of jobs and the setup times of machines required when a new job starts processing. Demand is set for each period. Over production incurs the holding cost. The problem is formulated as a fuzzy capacitated optimization problem with the objective to minimize the setup and holding costs. A simulated annealing algorithm was developed to search for the best schedule. Experimental results are presented to show the efficiency of the algorithm.
Manufacturing enterprises nowadays face the challenge of increasing energy prices and requirement... more Manufacturing enterprises nowadays face the challenge of increasing energy prices and requirements to reduce their emissions. Most reported work on reducing manufacturing energy consumption today focuses on the need to improve the efficiency of resources (machines) largely ignoring the potential for energy reducing on the system-level where the operational method can be employed as the energy saving approach. The advantage is clearly that the scheduling and planning approach can also be applied across existing legacy systems and does not require large investment. Therefore, a multi-objective scheduling method is developed in this paper with reducing energy consumption as one of the objectives. This research focuses on classical job shop environment which is widely used in the manufacturing industry. A model for the bi-objectives problem that minimises total electricity consumption and total weighted tardiness is developed and the Non-dominant Sorting Genetic Algorithm is employed as the solution to obtain the Pareto front. A case study based on a modified 10 Â 10 job shop is presented to show the effectiveness of the algorithm and to prove the feasibility of the model.
This document is the author's post-print version, incorporating any revisions agreed during the p... more This document is the author's post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it.
This paper presents HyFlex, a software framework for the development of cross-domain search metho... more This paper presents HyFlex, a software framework for the development of cross-domain search methodologies. The framework features a common software interface for dealing with different combinatorial optimisation problems and provides the algorithm components that are problem specific. In this way, the algorithm designer does not require a detailed knowledge of the problem domains and thus can concentrate his/her efforts on designing adaptive general-purpose optimisation algorithms. Six hard combinatorial problems are fully implemented: maximum satisfiability, one dimensional bin packing, permutation flow shop, personnel scheduling, traveling salesman and vehicle routing. Each domain contains a varied set of instances, including real-world industrial data and an extensive set of state-of-the-art problem specific heuristics and search operators. HyFlex represents a valuable new benchmark of heuristic search generality, with which adaptive cross-domain algorithms are being easily developed and reliably compared.This article serves both as a tutorial and a as survey of the research achievements and publications so far using HyFlex.
We present a hybrid approach of goal programming and meta-heuristic search to find compromise sol... more We present a hybrid approach of goal programming and meta-heuristic search to find compromise solutions for a difficult employee scheduling problem, i.e. nurse rostering with many hard and soft constraints. By employing a goal programming model with different parameter settings in its objective function, we can easily obtain a coarse solution where only the system constraints (i.e. hard constraints) are satisfied and an ideal objective-value vector where each single goal (i.e. each soft constraint) reaches its optimal value. The coarse solution is generally unusable in practise, but it can act as an initial point for the subsequent meta-heuristic search to speed up the convergence. Also, the ideal objective-value vector is, of course, usually unachievable, but it can help a multi-criteria search method (i.e. compromise programming) to evaluate the fitness of obtained solutions more efficiently. By incorporating three distance metrics with changing weight vectors, we propose a new time-predefined meta-heuristic approach, which we call the falling tide algorithm, and apply it under a multi-objective framework to find various compromise solutions. By this approach, not only can we achieve a trade off between the computational time and the solution quality, but also we can achieve a trade off between the conflicting objectives to enable better decision-making.
In an attempt to ensure good-quality printouts of our technical reports, from the supplied PDF fi... more In an attempt to ensure good-quality printouts of our technical reports, from the supplied PDF files, we process to PDF using Acrobat Distiller. We encourage our authors to use outline fonts coupled with embedding of the used subset of all fonts (in either Truetype or Type 1 formats) except for the standard Acrobat typeface families of Times, Helvetica (Arial), Courier and Symbol. In the case of papers prepared using TEX or LATEX we endeavour to use subsetted Type 1 fonts, supplied by Y&Y Inc., for the Computer Modern, Lucida Bright and Mathtime families, rather than the public-domain Computer Modern bitmapped fonts. Note that the Y&Y font subsets are embedded under a site license issued by Y&Y Inc.
To the extent reasonable and practicable the material made available in Nottingham ePrints has be... more To the extent reasonable and practicable the material made available in Nottingham ePrints has been checked for eligibility before being made available.
To the extent reasonable and practicable the material made available in Nottingham ePrints has be... more To the extent reasonable and practicable the material made available in Nottingham ePrints has been checked for eligibility before being made available.
International Journal of Production Economics, 2016
Increasing energy price and requirements to reduce emission are new challenges faced by manufactu... more Increasing energy price and requirements to reduce emission are new challenges faced by manufacturing enterprises. A considerable amount of energy is wasted by machines due to their underutilisation. Consequently, energy saving can be achieved by turning off the machines when they lay idle for a comparatively long period. Otherwise, turning the machine off and back on will consume more energy than leave it stay idle. Thus, an effective way to reduce energy consumption at the system level is by employing intelligent scheduling techniques which are capable of integrating fragmented short idle periods on the machines into large ones. Such scheduling will create opportunities for switching off underutilised resources while at the same time maintaining the production performance. This paper introduces a model for the bi-objective optimisation problem that minimises the total non-processing electricity consumption and total weighted tardiness in a job shop. The Turn off/Turn on is applied as one of the electricity saving approaches. A novel multi-objective genetic algorithm based on NSGA-II is developed. Two new steps are introduced for the purpose of expanding the solution pool and then selecting the elite solutions. The research presented in this paper is focused on the classical job shop environment, which is widely used in the manufacturing industry and provides considerable opportunities for energy saving. The algorithm is validated on job shop problem instances to show its effectiveness.
Radiotherapy treatment planning aims at delivering a sufficient radiation dose to cancerous tumou... more Radiotherapy treatment planning aims at delivering a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour-surrounding area. It is a time-consuming trial-and-error process that requires the expertise of a group of medical experts including oncologists and medical physicists and can take from 2 to 3h to a few days. Our objective is to improve the performance of our previously built case-based reasoning (CBR) system for brain tumour radiotherapy treatment planning. In this system, a treatment plan for a new patient is retrieved from a case base containing patient cases treated in the past and their treatment plans. However, this system does not perform any adaptation, which is needed to account for any difference between the new and retrieved cases. Generally, the adaptation phase is considered to be intrinsically knowledge-intensive and domain-dependent. Therefore, an adaptation often requires a large amount of domain-specific knowledge, which...
Many manufacturing companies in China currently are suffering from a Rolling Blackout policy for ... more Many manufacturing companies in China currently are suffering from a Rolling Blackout policy for the industry electricity supply which means that the government electricity is cut off several days in every week resulting in manufacturing companies illegally starting their own diesel generators to maintain production. However, the private generation of electricity is more polluting and costly than the government supplied resource. if they do not have access to multi-objective optimisation tools. The Non-dominant Sorting Genetic Algorithm has been used as the basis for solving the optimisation problem. Case studies based on four modified job shop instances have been studied to show the effectiveness of the proposed heuristic and the algorithm.
Ant colony optimisation, a constructive metaheuristic inspired by the foraging behaviour of ants,... more Ant colony optimisation, a constructive metaheuristic inspired by the foraging behaviour of ants, has been applied to a wide range of problems since its inception. Many of these are production scheduling problems such as the job shop, in which a collection of operations (grouped into jobs) must be scheduled for processing on different machines. In typical ACO applications, solutions are generated by constructing a permutation of the operations, from which a deterministic algorithm can generate the actual schedule. This paper considers an alternative approach in which each machine is assigned one of a number of alternative dispatching rules, which heuristically determines the processing order for that machine. This representation creates a substantially smaller search space that likely contains good solutions. The performance of both approaches is compared on a real-world job shop scheduling problem in which processing times and job due dates are modelled with fuzzy sets. Results indicate that the new approach produces better solutions more quickly than the traditional approach.
2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422)
This paper describes a new model for robust predictive/reactive scheduling of steel continuous ca... more This paper describes a new model for robust predictive/reactive scheduling of steel continuous casting based on the use of multi-agents, tabu search and heuristic approaches. A continuous caster agent generates a predictive production schedule taking into account manufacturing requirements and local constraints using tabu search. The predictive schedule is modified so as to minimise deviation between the performance measure values of the realised and predictive schedules in order to react to real-time events. We propose several schedule-repair and complete reschedule strategies to handle the real-time events, evaluate and compare their performance. The decision as to whether to locally repair the schedule or reschedule from scratch (complete reschedule) is based on three measures: robustness, utility and stability. Utility measures the change in schedule objective following schedule revision. Stability measures the deviation from the original schedule caused by schedule revision to quantify the undesirability of making large changes to the initial predictive schedule unless absolutely necessary. Robustness combines the utility and stability measures. In order to investigate the performance of these measures and strategies, simulation experiments were carried out and results are reported.
Steel production is a complex process and finding coherent and effective schedules for the wide v... more Steel production is a complex process and finding coherent and effective schedules for the wide variety of production steps, in a dynamic environment, is a challenging task. In this paper we propose a multi-agent architecture for integrated dynamic scheduling of the hot strip mill and the continuous caster. The scheduling systems of these processes have very different objectives and constraints, and operate in an environment where there is a substantial quantity of real-time information concerning production failures and customer requests. Each process is assigned to an agent which independently, seeks an optimal dynamic schedule at a local level taking into account local objectives, real-time information and information received from other agents. Each agent can react to real-time events in order to fix any problems that occur. We focus here, particularly, on the hot strip mill agent which uses a tabu search heuristic to create good predictive-reactive schedules quickly. The other agents simulate the production of the coil orders and the real-time events, which occur during the scheduling process. When real-time events occur on the hot strip mill, the hot strip mill agent might decide whether to repair the current schedule or reschedule from scratch. To address this problem, a range of schedule repair and complete rescheduling strategies are investigated and their performance is assessed with respect to measures of utility, stability and robustness, using an experimental simulation framework.
This paper presents a fuzzy approach to capacitated flow shop scheduling problem. Fuzzy sets are ... more This paper presents a fuzzy approach to capacitated flow shop scheduling problem. Fuzzy sets are applied to express the flexible constraints on capacity of each period in the scheduling horizon. Fuzzy sets are also used to model the processing times of jobs and the setup times of machines required when a new job starts processing. Demand is set for each period. Over production incurs the holding cost. The problem is formulated as a fuzzy capacitated optimization problem with the objective to minimize the setup and holding costs. A simulated annealing algorithm was developed to search for the best schedule. Experimental results are presented to show the efficiency of the algorithm.
Manufacturing enterprises nowadays face the challenge of increasing energy prices and requirement... more Manufacturing enterprises nowadays face the challenge of increasing energy prices and requirements to reduce their emissions. Most reported work on reducing manufacturing energy consumption today focuses on the need to improve the efficiency of resources (machines) largely ignoring the potential for energy reducing on the system-level where the operational method can be employed as the energy saving approach. The advantage is clearly that the scheduling and planning approach can also be applied across existing legacy systems and does not require large investment. Therefore, a multi-objective scheduling method is developed in this paper with reducing energy consumption as one of the objectives. This research focuses on classical job shop environment which is widely used in the manufacturing industry. A model for the bi-objectives problem that minimises total electricity consumption and total weighted tardiness is developed and the Non-dominant Sorting Genetic Algorithm is employed as the solution to obtain the Pareto front. A case study based on a modified 10 Â 10 job shop is presented to show the effectiveness of the algorithm and to prove the feasibility of the model.
This document is the author's post-print version, incorporating any revisions agreed during the p... more This document is the author's post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it.
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