Solving flow shop scheduling problem based on improved non-dominated genetic algorithm

Abstract Aiming at the multi-objective problem of flow workshop problem, a multi-objective optimization model was constructed and an improved non-dominated sorting genetic algorithm was proposed. Firstly, aiming at these problems, this paper proposes a two-stage chromosome coding method to adapt to the new production scenarios. Secondly, a new adaptive method is proposed to improve the convergence speed and the superiority of Pareto solution set. Finally, simulation results show that the optimality of the improved non-dominated sorting genetic algorithm is improved greatly.

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Multi-Objective Optimization Genetic Algorithm for Flow-Shop Scheduling Module by Using Fuzzy-AHP

2019 2nd World Conference on Mechanical Engineering and Intelligent Manufacturing (WCMEIM) ◽

10.1109/wcmeim48965.2019.00080 ◽

2019 ◽

Author(s):

Lan Cai ◽

Zhen Chen

Keyword(s):

Genetic Algorithm ◽

Flow Shop ◽

Fuzzy Ahp ◽

Flow Shop Scheduling ◽

Multi Objective Optimization ◽

Shop Scheduling ◽

Multi Objective

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A Proposed Genetic Algorithm Coding for Flow-Shop Scheduling Problems

International Journal of Computers Communications & Control ◽

10.15837/ijccc.2007.3.2356 ◽

2007 ◽

Vol 2 (3) ◽

pp. 229 ◽

Cited By ~ 12

Author(s):

Hela Boukef ◽

Mohamed Benrejeb ◽

Pierre Borne

Keyword(s):

Genetic Algorithm ◽

Flow Shop ◽

Flow Shop Scheduling ◽

Scheduling Problems ◽

Multi Objective Optimization ◽

Flowshop Scheduling ◽

Food Industries ◽

Shop Scheduling ◽

Multi Objective

A new genetic algorithm coding is proposed in this paper to solve flowshop scheduling problems. To show the efficiency of the considered approach, two examples, in pharmaceutical and agro-food industries are considered with minimization of different costs related to each problem as a scope. Multi-objective optimization is thus, used and its performances proved.

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Study on Multi-Objective Optimization of Hybrid Flow Shop Scheduling Problem

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1082.529 ◽

2014 ◽

Vol 1082 ◽

pp. 529-534

Author(s):

Zheng Ying Lin ◽

Wei Zhang

Keyword(s):

Flow Shop ◽

Economic Benefits ◽

Flow Shop Scheduling ◽

Hybrid Flow Shop ◽

Scheduling Problem ◽

Multi Objective Optimization ◽

Nsga Ii ◽

Shop Scheduling ◽

Multi Objective ◽

Hybrid Flow Shop Scheduling

Due to several mutual conflicting optimized objectives in the hybrid flow shop scheduling problem, its optimized model, including three objectives of make-span, flow-time and tardiness, was firstly set up, instead of the single optimized objective. Furthermore, in order to improve the optimized efficiency and parallelism, after comparing the normal multi-objective optimized methods, an improved NSGA-II algorithm with external archive strategy was proposed. Finally, taking a piston production line as example, its performance was tested. The result showed that the multi-objective optimization of hybrid flow shop scheduling based on improved NSGA-II provided managers with a set of feasible solutions for selection in accordance to their own preference. Therefore the decision could be made more scientific and efficient, and thus brings to the factory more economic benefits.

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