Title :
New Evolutionary Subset: Application to Symbiotic Evolutionary Algorithm for Job-Shop Scheduling Problem
Author :
Su, Zhaofeng ; Qiu, Hongze ; Zhu, Daming ; Feng, Haodi
Abstract :
Evolutionary algorithms (EAs) prove to be powerful in solving combinatorial optimization problems. Construction mechanism of evolutionary subset affects the search capacity and efficiency. In this paper, random evolutionary subset is proposed to promote EAs´ performance and compared with traditional neighborhood evolutionary subset. During the evolution process, evolutionary subsets are formed for localized evolution. To construct neighborhood evolutionary subset all individuals are chosen from a neighborhood in the population while in random evolutionary subset randomly. Two parameters affect the performance of neighborhood evolutionary subset: size and location. For random evolutionary subset, size is the only parameter that affects the evolution process and the suitable value is 6-15 on the basis of experimental results. The experimental results show the random evolutionary subset has better performance: showing high efficiency in getting much better solutions and fairly well solutions are obtained in early stage of evolution process.
Keywords :
combinatorial mathematics; evolutionary computation; job shop scheduling; optimisation; random processes; search problems; set theory; combinatorial optimization problem; evolutionary algorithm; job-shop scheduling problem; random evolutionary subset; search capacity; Application software; Conference management; Energy management; Evolution (biology); Evolutionary computation; Job shop scheduling; Manufacturing processes; Process planning; Processor scheduling; Symbiosis; evolutionary algorithm; evolutionary subset; job-shop scheduling problem;
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.2008.579