Earticle

초록

영어

The vehicle routing problem (VRP) is one of the most challenging problems in the op-timization of distribution. Genetic algorithm (GA) has been proved capable of solving VRPs. However, the resolution effectiveness of GA decreases with the increase of nodes within VRPs. It often appears premature convergence or poor ability of local search. In this paper, a hybrid genetic-monkey algorithm (HGMA), integrating monkey algorithm (MA) into genetic algorithm framework, is proposed to overcome the shortcomings above. Monkey climbing (A novel climb process is designed for VRP with discrete variables.) and somersault processes improve ability of local and global search. Furthermore, flexi-ble fitness function, through which infeasible solutions are allowed, are developed to ex-pand the search space. The experiment results indicate efficiency of the proposed algorithm.

목차

Abstract
 1. Introduction
 2. Formulation for VRP
 3. The Proposed HGMA for VRP
  3.1 Framework
  3.2 Coding and Fitness Function
  3.3 Crossover
  3.4 Mutation
  3.5 Climbing and Somersault Search
 4. Experimental Analysis
 5. Conclusion and Future Work
 References

키워드

저자

• Jiashan ZHANG [ Chongqing Vocational Institute of Engineering, JiangJin, Chongqing, China, College of Business Administration, Liaoning Technical University, Huludao, Liaoning, China ]
• Jun YI [ Chongqing Vocational Institute of Engineering, JiangJin, Chongqing, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605