Discrete logistics network design model under interval hierarchical OD demand based on interval genetic algorithm
来源期刊:中南大学学报(英文版)2013年第9期
论文作者:LI Li-hua(李利华) FU Zhuo(符卓) ZHOU He-ping(周和平) HU Zheng-dong(胡正东)
文章页码:2625 - 2634
Key words:uncertainty; interval planning; hierarchical OD; logistics network design; genetic algorithm
Abstract: Aimed at the uncertain characteristics of discrete logistics network design, an interval hierarchical triangular uncertain OD demand model based on interval demand and network flow is presented. Under consideration of the system profit, the uncertain demand of logistics network is measured by interval variables and interval parameters, and an interval planning model of discrete logistics network is established. The risk coefficient and maximum constrained deviation are defined to realize the certain transformation of the model. By integrating interval algorithm and genetic algorithm, an interval hierarchical optimal genetic algorithm is proposed to solve the model. It is shown by a tested example that in the same scenario condition an interval solution [3 275.3, 3 603.7] can be obtained by the model and algorithm which is obviously better than the single precise optimal solution by stochastic or fuzzy algorithm, so it can be reflected that the model and algorithm have more stronger operability and the solution result has superiority to scenario decision.
LI Li-hua(李利华)1, 2, FU Zhuo(符卓)2, ZHOU He-ping(周和平)1, HU Zheng-dong(胡正东)3
(1. School of Traffic and Transport Engineering, Changsha University of Science and Technology,
Changsha 410004, China;
2. School of Traffic and Transport Engineering, Central South University, Changsha 410075, China;
3. School of Politics and Public Administration, University of South China, Hengyang 421001, China)
Abstract:Aimed at the uncertain characteristics of discrete logistics network design, an interval hierarchical triangular uncertain OD demand model based on interval demand and network flow is presented. Under consideration of the system profit, the uncertain demand of logistics network is measured by interval variables and interval parameters, and an interval planning model of discrete logistics network is established. The risk coefficient and maximum constrained deviation are defined to realize the certain transformation of the model. By integrating interval algorithm and genetic algorithm, an interval hierarchical optimal genetic algorithm is proposed to solve the model. It is shown by a tested example that in the same scenario condition an interval solution [3 275.3, 3 603.7] can be obtained by the model and algorithm which is obviously better than the single precise optimal solution by stochastic or fuzzy algorithm, so it can be reflected that the model and algorithm have more stronger operability and the solution result has superiority to scenario decision.
Key words:uncertainty; interval planning; hierarchical OD; logistics network design; genetic algorithm