An iterated metaheuristic for the directed network design problem with relays

被引:4
|
作者
Li, Xiangyong [1 ]
Lin, Shaochong [1 ]
Chen, Si [2 ]
Aneja, Y. P. [3 ]
Tian, Peng [4 ]
Cui, Youzhi [5 ]
机构
[1] Tongji Univ, Sch Econ & Management, Shanghai 200092, Peoples R China
[2] Murray State Univ, Arthur J Bauernfeind Coll Business, Murray, KY 42071 USA
[3] Univ Windsor, Odette Sch Business, Windsor, ON, Canada
[4] Shanghai Jiao Tong Univ, Antai Coll Econ & Management, Shanghai 200052, Peoples R China
[5] IBM China, 399 Keyuan Rd, Shanghai 201203, Peoples R China
关键词
Network design; Relay; Cycle-based neighborhood; Tabu search; Iterated metaheuristic; HYBRID GENETIC ALGORITHM;
D O I
10.1016/j.cie.2017.08.036
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
We study the directed network design problem with relays (DNDR), which arises in telecommunications and distribution systems where relay points are necessary. Given a directed network and a set of commodities, the DNDR consists of introducing a subset of arcs and locating relays on a subset of nodes such that in the resulting network, the total cost (arc cost plus relay cost) is minimized, and there exists a path linking the origin and destination of each commodity, in which the distances between the origin and the first relay, any two consecutive relays, and the last relay and the destination do not exceed a predefined distance limit. Since the DNDR is an NP-hard problem, we present an iterated metaheuristic based on tabu search, which iteratively solves the DNDR within two steps: generating paths for commodities, and determining optimal relay assignment associated with these paths. A cycle-based neighborhood is designed to generate neighboring solutions by replacing subpaths in commodities' paths with new ones. Given one sub path, the new substituting subpath is found by solving a shortest path problem between its two endpoints, explicitly taking into account the impact of opening one subpath on the objective value. For each neighboring solution, the associated relay allocation is determined by exactly determined. With a set of benchmark instances and newly generated instances, we compare our approach with other available algorithms. Computational results demonstrate that our proposed algorithm is an efficient method for the DNDR. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:35 / 45
页数:11
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