Title :
An Orthogonal Genetic Algorithm for Job Shop Scheduling Problems with Multiple Objectives
Author :
Feng, Ming-yue ; Yi, Xian-qing ; LI, Guo-hui ; Tang, Shao-xun ; He, Jun
Author_Institution :
Coll. of Inf. Syst. & Manage., Nat. Univ. of Defense Technol., Changsha
Abstract :
The job shop scheduling problem with multiple objectives is a research hotspot. In this paper, a multi-objective orthogonal genetic algorithm(MOOGA) was proposed to solve this problem. MOOGA integrated the orthogonal design method into the crossover operator, which could generate both outstanding and evenly distributed filial individuals, and improve the efficiency of the algorithm. A fitness calculating method was designed to help MOOGA move towards the Pareto front. Numerical results verify effectiveness and efficiency of the algorithm.
Keywords :
Pareto optimisation; genetic algorithms; job shop scheduling; mathematical operators; Pareto front; crossover operator; fitness calculating method; job shop scheduling; multiobjective orthogonal genetic algorithm; Conference management; Costs; Delay effects; Design methodology; Educational institutions; Genetic algorithms; Helium; Information management; Job shop scheduling; Management information systems; Job Shop Scheduling; Orthogonal Genetic Algorithm; multi-objective;
Conference_Titel :
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-0-7695-3304-9
DOI :
10.1109/ICNC.2008.612
