An E2GPGP-GASA-Based Multi-Agent Job Shop Scheduling System
In this paper,a job shop scheduling model combining MAS (Multi-Agent System) with GASA (Simulated Annealing-Genetic Algorithm) is presented.The proposed model is based on the E2GPGP (extended extended generalized partial global planning) mechanism and utilizes the advantages of static intelligence algorithms with dynamic MAS.A scheduling process from initialized macro-scheduling to repeated micro-scheduling is designed for largescale complex problems to enable to implement an effective and widely applicable prototype system for the job shop scheduling problem (JSSP).Under a set of theoretic strategies in the GPGP which is summarized in detail,E2GPGP is also proposed further.The GPGPcooperation-mechanism is simulated by using simulation software DECAF for the JSSP.The results show that the proposed model based on the E2GPGP-GASA not only improves the effectiveness,but also reduces the resource cost.
job shop scheduling problem simulated annealing-genetic algorithm:multi-agent system extended extended generalized partial global planning
Lu Linlin Ma Xin Wang Yaxuan
Software College,Dalian University of Foreign Language Dalian,China College of Computer Science and Technology,Jilin University Changchun,China
国际会议
太原
英文
343-347
2011-02-26（万方平台首次上网日期，不代表论文的发表时间）