Title :
A multi-objective imperialist competitive algorithm to solve a new multi-modal tree hub location problem
Author :
Tavakkoli-Moghaddam, R. ; Sedehzadeh, Samaneh
Author_Institution :
Sch. of Ind. Eng. & Res., Univ. of Tehran, Tehran, Iran
fDate :
July 30 2014-Aug. 1 2014
Abstract :
A hub location problem is a main group of the transportation network, which is utilized as a connecting and switching point for demand between origins and destinations. Recently, a tree hub location problem has been introduced as an incomplete hub network with single assignment, in which hubs are connected by means of a tree. This paper presents a new bi-objective, multi-modal tree hub location problem with different capacity levels. Besides the location and allocation decisions in tree hub network, this model decides on transportation modes and capacity levels such that the total transportation cost and time are minimized. Additionally, a multi-objective imperialist competitive algorithm (MOICA) is proposed to solve the presented model and obtain Pareto-optimal solutions of the given problem. Finally, the performance of this algorithm is compared with a non-dominated sorting genetic algorithm (NSGA-II).
Keywords :
Pareto optimisation; cost reduction; transportation; trees (mathematics); MOICA; Pareto-optimal solutions; allocation decision; biobjective tree hub location problem; capacity levels; incomplete hub network; multimodal tree hub location problem; multiobjective imperialist competitive algorithm; time minimisation; total transportation cost minimisation; transportation modes; transportation network; Genetic algorithms; Modems; Switches; imperialist competitive algorithm; multi-objective optimization; transportation mode; tree hub location;
Conference_Titel :
Nature and Biologically Inspired Computing (NaBIC), 2014 Sixth World Congress on
Conference_Location :
Porto
Print_ISBN :
978-1-4799-5936-5
DOI :
10.1109/NaBIC.2014.6921878