Journal ArticleDOI
A hybrid method for solving stochastic job shop scheduling problems
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TLDR
A hybrid method using a neural network approach to generate initial feasible solutions and then a simulated annealing algorithm to improve the quality and performance of the initial solutions in order to produce the optimal/near-optimal solution.About:
This article is published in Applied Mathematics and Computation.The article was published on 2005-11-01. It has received 92 citations till now. The article focuses on the topics: Flow shop scheduling & Job shop scheduling.read more
Citations
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Journal ArticleDOI
Multiobjective evolutionary algorithm for manufacturing scheduling problems: state-of-the-art survey
Mitsuo Gen,Lin Lin +1 more
TL;DR: This paper focuses on the design of multiobjective evolutionary algorithms (MOEAs) to solve a variety of scheduling problems, and introduces fitness assignment mechanism and performance measures for solving multiple objective optimization problems.
Journal ArticleDOI
A novel competitive co-evolutionary quantum genetic algorithm for stochastic job shop scheduling problem
TL;DR: A novel competitive co-evolutionary quantum genetic algorithm that could not only adjust population size dynamically to increase the diversity of genes and avoid premature convergence, but also accelerate the convergence speed with Q-bit representation and quantum rotation gate is proposed.
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A new hybrid multi-objective Pareto archive PSO algorithm for a bi-objective job shop scheduling problem
TL;DR: This paper presents a new mathematical model for a bi-objective job shop scheduling problem with sequence-dependent setup times and ready times that minimizes the weighted mean flow time ([email protected]?"w) and total penalties of tardiness and earliness (E/T).
Journal ArticleDOI
A novel parallel quantum genetic algorithm for stochastic job shop scheduling
TL;DR: In this article, a novel parallel quantum genetic algorithm (NPQGA) is proposed for the stochastic job shop scheduling problem with the objective of minimizing the expected value of makespan, where the processing times are subjected to independent normal distributions.
Journal ArticleDOI
Development of a simulation-based decision support system for controlling stochastic flexible job shop manufacturing systems
TL;DR: A simulation-based decision support system (DSS) to production control of a stochastic flexible job shop (SFJS) manufacturing system by integrating a real-time simulator and a rule-based DSS.
References
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Book
Theory of scheduling
TL;DR: Reading theory of scheduling as one of the reading material to finish quickly to increase the knowledge and happiness in your lonely time.
Journal ArticleDOI
Neural Networks for Combinatorial Optimization: a Review of More Than a Decade of Research
TL;DR: It has been over a decade since neural networks were first applied to solve combinatorial optimization problems and the current standing of neural networks for combinatorsial optimization is presented by considering each of the major classes of combinatorially optimization problems.
Reference EntryDOI
Survey of Job Shop Scheduling Techniques
TL;DR: The sections in this article are: Dispatching Rules, Fuzzy Logic, Swarm, Reactive Scheduling, Theory of Constraints, and Summary and Conclusions.
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Fuzzy constraints in job-shop scheduling
TL;DR: An extension of the constraint-based approach to job-shop scheduling that accounts for the flexibility of temporal constraints and the uncertainty of operation durations is proposed, including fuzzy extensions of well-known look-ahead schemes.
Journal ArticleDOI
Job-shop scheduling using neural networks
Anant Singh Jain,Sheik Meeran +1 more
TL;DR: Major contributions in solving PiG using a Hopfield neural network, as well as applications of back-error propagation to general scheduling problems are presented.