A Bee Evolutionary Guiding Nondominated Sorting Genetic Algorithm II for Multiobjective Flexible Job-Shop Scheduling
نویسندگان
چکیده
منابع مشابه
A Bee Evolutionary Guiding Nondominated Sorting Genetic Algorithm II for Multiobjective Flexible Job-Shop Scheduling
Flexible job-shop scheduling problem (FJSP) is an NP-hard puzzle which inherits the job-shop scheduling problem (JSP) characteristics. This paper presents a bee evolutionary guiding nondominated sorting genetic algorithm II (BEG-NSGA-II) for multiobjective FJSP (MO-FJSP) with the objectives to minimize the maximal completion time, the workload of the most loaded machine, and the total workload ...
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Flexible Job shop scheduling is very important in production management and combinatorial optimization. It is NP-hard problem and consists of two sub-problems: sequencing and assignment. Multiobjective Flexible Job-Shop Scheduling Problems (MFJSSP) is formulated as three-objective problem which minimizes completion time (makespan), critical machine workload and total work load of all machines. ...
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This paper addresses the flexible job shop scheduling problem with minimization of the makespan, maximum machine workload, and total machine workload as the objectives. A multiobjective memetic algorithm is proposed. It belongs to the integrated approach, which deals with the routing and sequencing sub-problems together. Dominance-based and aggregation-based fitness assignment methods are used ...
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— Flexible Job Shop scheduling problem (FJSSP) is an important scheduling problem which has received considerable importance in the manufacturing domain. In this paper a genetic algorithm (GA) based scheduler is presented for flexible job shop problem to minimise makespan. The proposed approach implements a domain independent GA to solve this important class of problem. The scheduler is impleme...
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ژورنال
عنوان ژورنال: Computational Intelligence and Neuroscience
سال: 2017
ISSN: 1687-5265,1687-5273
DOI: 10.1155/2017/5232518