A Multi-agent Model Based on Hybrid Genetic Algorithm for Job Shop Scheduling Problem with Generic Time Lags

2017 ◽  
Author(s):  
Madiha Harrabi ◽  
Olfa Belkahla Driss ◽  
Khaled Ghedira
Keyword(s):  
Job Shop ◽  
Job Shop Scheduling ◽  
Hybrid Genetic Algorithm ◽  
Time Lags ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Agent Model ◽  
Shop Scheduling ◽  
Multi Agent ◽  
Generic Time

Study on Scheduling Optimization for Flexible Job Shop

2010 ◽  
Vol 26-28 ◽  
pp. 821-825 ◽  
Author(s):  
Xiao Xia Liu ◽  
Chun Bo Liu ◽  
Ze Tao
Keyword(s):  
Job Shop ◽  
Job Shop Scheduling ◽  
Hybrid Genetic Algorithm ◽  
Utilization Rate ◽  
Flexible Job Shop ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Multi Objective ◽  
Pareto Ranking

A hybrid genetic algorithm based on Pareto was proposed and applied to flexible job shop scheduling problem (FJSP) with multi-objective, and the multi-objective FJSP optimization model was built, where the make-span and the machine utilization rate were concerned. The algorithm embeds Pareto ranking strategy into Pareto competition method. The operation-based encoding and an active scheduling decoding method are employed. In order to promote solution diversity, the niche technology and many kinds of crossover operations are used. Pareto filter saves the optimum individual occurring in the course of evolution, which avoids losing the optimum solutions. Three simulation experiments are carried out to illustrate that the proposed method could solve multi-objective job shop scheduling problem effectively.

scholarly journals Extended Hybrid Genetic Algorithm for Solving Job Shop Scheduling Problem

2021 ◽  
Vol 10 (02) ◽  
pp. 017-020
Author(s):  
Sumaia E. Eshim ◽  
Mohammed M. Hamed
Keyword(s):  
Genetic Algorithm ◽  
Hybrid Algorithm ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Hybrid Genetic Algorithm ◽  
Benchmark Problems ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Solution Quality ◽  
Shop Scheduling

In this paper, a hybrid genetic algorithm (HGA) to solve the job shop scheduling problem (JSSP) to minimize the makespan is presented. In the HGA, heuristic rules are integrated with genetic algorithm (GA) to improve the solution quality. The purpose of this research is to investigate from the convergence of a hybrid algorithm in achieving a good solution for new benchmark problems with different sizes. The results are compared with other approaches. Computational results show that a hybrid algorithm is capable to achieve good solution for different size problems.

Sign in / Sign up

Export Citation Format

Share Document