A Generic Mechanism for Repairing Job Shop Schedules

International Journal of Human-Computer Studies, 1995

Practical scheduling usually has to react to many unpredictable events and uncertainties in the production environment. Although often possible in theory, it is undesirable to reschedule from scratch in such cases. Since the surrounding organization will be prepared for the predicted schedule it is important to change only those features of the schedule that are necessary. We show how on one side fuzzy logic can be used to support the construction of schedules that are robust with respect to changes due to certain types of event. On the other side we show how a reaction can be restricted to a small environment by means of fuzzy constraints and a repair-based problem-solving strategy. We demonstrate the proposed representation and problem-solving method by introducing a scheduling application in a steelmaking plant. We construct a preliminary schedule by taking into account only the most likely duration of operations. This schedule is iteratively "repaired" until some threshold evaluation is found. A repair is found with a local search procedure based on Tabu Search. Finally, we show which events can lead to reactive scheduling and how this is supported by the repair strategy.

In today's competitive environment rescheduling is a necessary evil in case of shop floor disturbances like machine breakdown. This paper gives a robust rescheduling strategy to deal with such situation in the flexible job shop environment. An effective use of Genetic Algorithm (GA) and scheduling rules is done with the adaptive crossover and mutation to obtain a feasible schedule as well as reschedule. An innovative approach for rescheduling is adopted to deal with the machine breakdown. This gives management an ease of assigning jobs' operations to different work centers. This paper also solves the benchmark problem MT10 for different instances in Flexible Job Shop environment for rescheduling in case of machine breakdown. Results of simulation studies for scheduling and rescheduling are also given by using developed software for comparison purpose.

2008

Machine disruptions C max change for 10x10 'abz' problems. .. .. . 5 Machine disruptions C max change for 20x15 'abz' problems. .. .. . 6 Machine disruptions C max change for 11x5 & 10x6 'car' problems. . 7 Machine disruptions C max change for 6x6 & 20x5 'mt' problems. .. 8 Machine disruptions C max change for 11x5 & 13x4 'orb' problems. . 9 Machine-robustness as a % change in makespan. .. .. .. .. .. . 10 Location values for slack policies for job release-time disruptions. . .

Computers & Industrial Engineering, 2007

... and make a judgment whether or not we should conduct schedule revision at each individual ... with much expense for its operations and, instead, makes the system behavior hard to predict ...Shafaei and Brunn (1999) examined the performance of dispatching rules on the periodic ...

International Journal of Simulation Modelling, 2013

In this paper, Selective Rerouting (SR) approach based on lateral entry of critical jobs in the queue of alternate machine is used to minimize the mean tardiness of the jobs in flexible job shop. Further, the efficacy of selective rerouting algorithm has been investigated by comparing it to the rerouting policies. Simulation studies using ProModel simulation software were carried out at different breakdown levels, mean time to repair levels, utilization levels of flexible job shop, due date tightness levels involving a total of 600 simulation runs. Each run of simulation spans for a period of 2000 completed jobs. The results establish that the proposed selective rerouting approach is better than other reported rerouting approaches as it improves 69.92 %, 69.31 %, 65.33 %, and 44.27 % mean tardiness compared with no rerouting, queue rerouting, arrival rerouting and all rerouting approaches respectively. It is seen that irrespective of the breakdown level in the investigated range, reduction of mean tardiness decreases in no rerouting, all rerouting, queue rerouting and arrival rerouting in the above order.

2016 International Conference on Control, Decision and Information Technologies (CoDIT), 2016

Many disturbances can occur during the execution of a manufacturing scheduling process. To cope with this drawback, flexible solutions are proposed based on the offline and the online phase of the schedule. Groups of permutable operations is one of the most studied flexible scheduling methods bringing flexibility as well as quality to a schedule. The online phase of this method is based on a human-machine system allowing to choose in real-time one schedule from a set of schedules that fits best the real state of the system. In this paper, we propose and evaluate a new criterion called the best-case in order to be used in real-time during the online phase of the groups of permutable operations. This criterion offers an optimal or near-optimal solution from a set of solutions. The usefulness of this criterion is showed using a comparative review with two other criteria on a benchmark instances using the maximum tardiness objective.

Algorithms, 2019

The job shop scheduling problem with blocking constraints and total tardiness minimization represents a challenging combinatorial optimization problem of high relevance in production planning and logistics. Since general-purpose solution approaches struggle with finding even feasible solutions, a permutation-based heuristic method is proposed here, and the applicability of basic scheduling-tailored mechanisms is discussed. The problem is tackled by a local search framework, which relies on interchange- and shift-based operators. Redundancy and feasibility issues require advanced transformation and repairing schemes. An analysis of the embedded neighborhoods shows beneficial modes of implementation on the one hand and structural difficulties caused by the blocking constraints on the other hand. The applied simulated annealing algorithm generates good solutions for a wide set of benchmark instances. The computational results especially highlight the capability of the permutation-based...

We consider the single machine scheduling problem with dynamic job arrival and total weighted tardiness and makespan as objective functions. The machine is subject to disruptions related to late raw material arrival and machine breakdowns. We propose a proactive-reactive approach to deal with possible perturbations. In the proactive phase, instead of providing only one schedule to the decision maker, we present a set of predictive schedules. This set is characterized by a partial order of jobs and a type of associated schedules, here semi-active schedules. This allows to dispose of some flexibility in job sequencing and flexibility in time that can be used on-line by the reactive algorithm to hedge against unforeseen disruptions. We conduct computational experiments which prove that our approach outperforms a predictive reactive approach particularly for disruptions with low to medium amplitude.

2020

In this paper, a new mathematical programming model is proposed for a partial flexible job shop scheduling problem with an integrated solution approach. The purpose of this model is the assignment of production operations to machines with the goal of simultaneously minimizing operating costs and penalties. These penalties include delayed delivery, deviation from a fixed time point for preventive maintenance, and deviation from the priorities of each machine. Considering the priorities for machines in partial flexible job shop scheduling problems can be a contribution in closer to the reality of production systems. For validation and evaluation of the effectiveness of the model, several numerical examples are solved by using the Baron solver in GAMS. Sensitivity analysis is performed for the model parameters. The results further indicate the relationship between scheduling according to priorities of each machine and production scheduling.

International Journal of Production Research, 2013

This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae, and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material.