论文信息 - An Improved Artificial Bee Colony Algorithm for Job Shop Problem

An Improved Artificial Bee Colony Algorithm for Job Shop Problem

Job shop scheduling problem (JSP) plays a significant role for production management and combinatorial optimization. An improved artificial bee colony (IABC) algorithm with mutation operation is presented to solve JSP in this paper. The results for some benchmark problems reveal that IABC is effective and efficient compared to those of other approaches. IABC seems to be a powerful tool for optimizing job shop scheduling problem.

[1] Huang Ya-ping,et al. A Study of Job-shop Scheduling Problem Based on Improved Ant Colony Algorithm and Its Simulations , 2009 .

[2] D. Karaboga,et al. On the performance of artificial bee colony (ABC) algorithm , 2008, Appl. Soft Comput..

[3] Ling Wang,et al. A Modified Genetic Algorithm for Job Shop Scheduling , 2002 .

[4] John H. Holland,et al. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[5] Bin Yu,et al. Genetic Algorithm for Bus Frequency Optimization , 2010 .

[6] Hong Zhou,et al. The hybrid heuristic genetic algorithm for job shop scheduling , 2001 .

[7] H Rong Hwa,et al. ANT COLONY SYSTEM FOR JOB SHOP SCHEDULING WITH TIME WINDOWS , 2008 .

[8] Chuntian Cheng,et al. Optimizing the distribution of shopping centers with parallel genetic algorithm , 2007, Eng. Appl. Artif. Intell..

[9] Dervis Karaboga,et al. AN IDEA BASED ON HONEY BEE SWARM FOR NUMERICAL OPTIMIZATION , 2005 .

[10] Wang Wan. HOPFIELD NEURAL NETWORK APPROACH FOR JOB-SHOP SCHEDULING PROBLEMS , 2002 .

[11] Baozhen Yao,et al. Production , Manufacturing and Logistics An improved ant colony optimization for vehicle routing problem , 2008 .

[12] P. Aravindan,et al. A Tabu Search Algorithm for Job Shop Scheduling , 2000 .