Job-shop scheduling using neural networks

Jain, Anant; Meeran, Sheik

doi:10.1080/002075498193309

Cited by 76 publications

(36 citation statements)

References 57 publications

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“…The machine cannot be kept idle. 16. The number of workers assigned to each machine needs to be decided before any job can be processed and they will not be reassigned until all the jobs have been completed.…”

Section: Identical Parallel-machine Processing Worker Assignment Schmentioning

confidence: 99%

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Minimizing total flow time for the worker assignment scheduling problem in the identical parallel-machine models

Hu¹

2004

Int J Adv Manuf Technol

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The worker assignment scheduling problem consists of two basic questions of job scheduling and worker assignment. In this study, only the performance measure of total flow time is investigated in the model of identical parallel-machine with nonpreemptive jobs. Because the worker assignment scheduling problem in this specific model can be shown as NP-complete, heuristics have been developed for minimizing the total flow time. This selected worker assignment scheduling problem is solved in two stages of job scheduling and worker assignment. The shortest processing time for A i part (SPT-A) heuristic is used for the stage of job scheduling. For the stage of worker assignment, the largest marginal contribution (LMC) procedure is used to minimize the total flow time. Two 100 I/P/n/m/W problems were simulated; results obtained by the heuristics are either optimal or near optimal. In conclusion, the heuristics developed have shown very impressive results quite efficiently.

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Section: Identical Parallel-machine Processing Worker Assignment Schmentioning

confidence: 99%

“…Jansen et al [17] proposed a polynomial time approximation scheme to minimize the makespan. Yamada and Nakeno [23] and Jain and Meeran [16] used different methods, such as fuzzy decision-making and simulated annealing combined with deterministic local search, to solve specific problems.…”

Section: Introductionmentioning

confidence: 99%

Minimizing total flow time for the worker assignment scheduling problem in the identical parallel-machine models

Hu¹

2004

Int J Adv Manuf Technol

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“…Sule and Vijayasundaram [11] specifically dealt with a different scheduling problem that involved n jobs in m machine centres where each machine centre may have k number of identical processors. Iwamoto [12], Yamada and Nakeno [13], and Jain and Meeran [14] used different methods, such as fuzzy decision-making, deterministic local search, and neural networks, to solve specific problems.…”

Section: Scheduling Problem In the Model Of Identical Parallel Machinesmentioning

confidence: 99%

Minimising total tardiness for the worker assignment scheduling problem in identical parallel-machine models

Hu¹

2004

The International Journal of Advanced Manufacturing Technology

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The worker assignment scheduling problem involves both the decisions of job scheduling and worker assignment. In this research, only the performance measure of total tardiness is investigated in the model of identical parallel machines with nonpreemptive jobs. Since the worker assignment scheduling problem in the selected model can be shown to be NP-complete, heuristics have been developed for minimising the total tardiness. The worker assignment scheduling problem is solved in two phases of job scheduling and worker assignment. The SES (SPT, EDD, SLACK) heuristic is used for the phase of job scheduling. For the phase of worker assignment, the largest marginal contribution (LMC) procedure is used to minimise the total tardiness. From the simulation conducted, 88 out of 100 simulated problems yielded optimal solutions while the others also obtained very good results. In conclusion, the heuristics developed have shown very impressive results in both effectiveness and efficiency aspects.

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“…Most integer programming problems are solved by Branch & Bound (B&B) since Simplex does not return solutions for y ipk in integral form for equations (5) and (6) . The Iterative Linear Programming with Integer Adjustments (ILPIA) technique [3] resolves this by iteratively solving the LP twice, hence removing the need to specifically apply integer linear programming methods.…”

Section: A Linear Program For the Fjspmentioning

confidence: 99%

“…However, Jain and Meeran [6] pointed out some setbacks of the Hopfield approach. Firstly, the network produces many infeasible solutions or schedules which violates the JSP constraints.…”

Section: Introductionmentioning

confidence: 99%

Combining simplex with niche-based evolutionary computation for job-shop scheduling

Kuah

Tay

2006

Proceedings of the 8th Annual Conference on Genetic and Evolutionary Computation

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We propose a hybrid algorithm (called ALPINE) between Genetic Algorithm and Dantzig's Simplex method to approximate optimal solutions for the Flexible Job-Shop Problem. Locally, Simplex is extended for the JSP linear program to reduce the number of infeasible solutions while solution quality is improved with an operation order search. Globally, a niche-based evolutionary strategy is employed to gain parallelization while solution diversity is maintained in two ways; composite dispatching rulebased population initialization and memory-based machine assignment. Performance results on benchmark problems show that ALPINE outperforms existing hybrid techniques with a new global optima found for the 10x7 Flexible Job Shop Problem.

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Job-shop scheduling using neural networks

Cited by 76 publications

References 57 publications

Minimizing total flow time for the worker assignment scheduling problem in the identical parallel-machine models

Minimizing total flow time for the worker assignment scheduling problem in the identical parallel-machine models

Minimising total tardiness for the worker assignment scheduling problem in identical parallel-machine models

Combining simplex with niche-based evolutionary computation for job-shop scheduling

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