Book ChapterDOI
An Effective Chromosome Representation for Evolving Flexible Job Shop Schedules
Joc Cing Tay,Djoko Wibowo +1 more
- pp 210-221
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TLDR
A new chromosome representation and a design of related parameters to solve the FJSP efficiently are posed and empirical experiments show that the pro- posed chromosome representation obtains better results than the others in both quality and processing time required.Abstract:
As the Flexible Job Shop Scheduling Problem (or FJSP) is strongly NP-hard, using an evolutionary approach to find near-optimal solutions re- quires effective chromosome representations as well as carefully designed pa- rameters for crossover and mutation to achieve efficient search This paper pro- poses a new chromosome representation and a design of related parameters to solve the FJSP efficiently The results of applying the new chromosome repre- sentation for solving the 10 jobs x 10 machines FJSP are compared with three other chromosome representations Empirical experiments show that the pro- posed chromosome representation obtains better results than the others in both quality and processing time requiredread more
Citations
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Journal ArticleDOI
A genetic algorithm for the Flexible Job-shop Scheduling Problem
TL;DR: A genetic algorithm for the Flexible Job-shop Scheduling Problem (FJSP) integrates different strategies for generating the initial population, selecting the individuals for reproduction and reproducing new individuals to prove that genetic algorithms are effective for solving FJSP.
Journal ArticleDOI
Evolving dispatching rules using genetic programming for solving multi-objective flexible job-shop problems
Joc Cing Tay,Nhu Binh Ho +1 more
TL;DR: Experimental results show that composite dispatching rules generated by the genetic programming framework outperforms the single dispatches rules and composite dispatch rules selected from literature over five large validation sets with respect to minimum makespan, mean tardiness, and mean flow time objectives.
Journal ArticleDOI
An effective genetic algorithm for the flexible job-shop scheduling problem
Guohui Zhang,Liang Gao,Yang Shi +2 more
TL;DR: An improved chromosome representation is used to conveniently represent a solution of the FJSP, and different strategies for crossover and mutation operator are adopted.
Journal ArticleDOI
An Improved Genetic Algorithm for the Distributed and Flexible Job-shop Scheduling problem
TL;DR: An Improved Genetic Algorithm to solve the Distributed and Flexible Job-shop Scheduling problem is proposed and has been compared with other algorithms for distributed scheduling and evaluated with satisfactory results on a large set of distributed-and-flexible scheduling problems derived from classical job-shop scheduling benchmarks.
Journal ArticleDOI
Robust and stable flexible job shop scheduling with random machine breakdowns using a hybrid genetic algorithm
Nasr Al-Hinai,Tarek Y. ElMekkawy +1 more
TL;DR: A two-stage Hybrid Genetic Algorithm is proposed to generate the predictive schedule, which optimizes the primary objective, minimizing makespan in this work, where all the data is considered to be deterministic with no expected disruptions.
References
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Journal ArticleDOI
An Effective Heuristic Algorithm for the Traveling-Salesman Problem
S. Lin,Brian W. Kernighan +1 more
TL;DR: This paper discusses a highly effective heuristic procedure for generating optimum and near-optimum solutions for the symmetric traveling-salesman problem based on a general approach to heuristics that is believed to have wide applicability in combinatorial optimization problems.
Journal ArticleDOI
Deterministic job-shop scheduling: Past, present and future
Anant Singh Jain,Sheik Meeran +1 more
TL;DR: A subclass of the deterministic job-shop scheduling problem in which the objective is minimising makespan is sought, by providing an overview of the history, the techniques used and the researchers involved.
Journal ArticleDOI
Approach by localization and multiobjective evolutionary optimization for flexible job-shop scheduling problems
TL;DR: Two new approaches to solve jointly the assignment and job-shop scheduling problems (with total or partial flexibility) are presented and an evolutionary approach controlled by the assignment model is generated.