نویسندگان | هادی مختاری |
---|---|
نشریه | NEURAL COMPUT APPL |
نوع مقاله | Full Paper |
تاریخ انتشار | ۰-۰-۰۱ |
رتبه نشریه | ISI |
نوع نشریه | چاپی |
کشور محل چاپ | ایران |
نمایه نشریه | ISI ,SCOPUS ,Inspec |
چکیده مقاله
A reconfigurable manufacturing system is usually designed for quick re-adjusting of production capacity in response to market changes. In this paper we study a flow shop sequencing problem (FSSP) with controllable processing times as a special case of reconfigurable manufacturing system. It is possible to speed up the processing times through assign of additional resources or control of machine speed. After formulating this problem mathematically, a novel evolutionary procedure, entitled group search optimizer (GSO) is devised as solution method. The adapted GSO is a population based search tool which is devised based on the producer and scrounger behavior. GSO emphasizes on imitating searching model of real-world animals. The basic GSO with four promising improvements is elaborated and discussed for addressing the FSSP with controllable processing times. A set of computational experiments is also conducted to demonstrate the applicability of proposed FSSP and performance of improved GSOs.