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Research on Artificial Bee Colony and Its Application in Scheduling Problems

Author: LiuZuoZuo
Tutor: LiuXiangQian
School: Beijing Jiaotong University
Course: Pattern Recognition and Intelligent Systems
Keywords: ABC complexity performance Job-Shop permutation andcombination
CLC: TB497
Type: Master's thesis
Year: 2014
Downloads: 46
Quote: 0
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Abstract


Job-Shop scheduling problem (JSSP) is a resource allocation problem with constraint sequence requirement and task allocation. Attention is widely attracted for its important role in improving the production efficiency and in reducing the production cost. However, cause the job-shop scheduling problem is a typical NP-hard problem, optimal solutions can still not be precisely obtained by far. Artificial Bee Colony algorithm (ABC) is a new type of swarm intelligence algorithm. It is proposed according to the honey bee colonies in nature. The algorithm itself has advantages in stochastic initialization, low setting parameters, easy implementation and strong robustness etc. So research on ABC algorithm for JSSP have great theoretical significance and practical value.Firstly, the basic principle and current research status of ABC is introduced. The main contributions are listed as follows:a) For the first time, time and space complexity of ABC, GA, ACO and PSO are compared, pointing out that although the basic ABC algorithm does really have advantages in dealing with optimization problems while comparing with other three algorithms, it is still not suitable for solving JSSP.b) According to the classic mathematical model of Job-Shop problem combining with permutation optimization and combinational optimization feature of the JSSP, a new mathematical model based on permutation and combination is proposed.c) Based on the proposed model, the basic ABC algorithm is improved from the aspect of initialization, adjacent domain search, fitness calculation, etc., making it suitable for solving the JSSP. At last, the effectiveness of the improved ABC algorithm for solving Job Shop scheduling problem is verified through the simulation of typical Job-Shop problem experiments.

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