A Multi-Objective Imperialist Competitive Algorithm to Solve a New Multi-Modal Tree Hub Location Problem

被引:0
|
作者
Tavakkoli-Moghaddam, Reza [1 ,2 ]
Sedehzadeh, Samaneh [3 ]
机构
[1] Univ Tehran, Sch Ind Engn, Tehran, Iran
[2] Univ Tehran, Res Inst Energy Management & Planning, Coll Engn, Tehran, Iran
[3] Islamic Azad Univ, South Tehran Branch, Sch Ind Engn, Tehran, Iran
关键词
tree hub location; transportation mode; multi-objective optimization; imperialist competitive algorithm;
D O I
暂无
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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).
引用
收藏
页码:202 / 207
页数:6
相关论文
共 50 条
  • [31] Multi-Objective Modified Imperialist Competitive Algorithm for Brushless DC Motor Optimization
    Sharifi, MohammadAli
    Mojallali, Hamed
    IETE JOURNAL OF RESEARCH, 2019, 65 (01) : 96 - 103
  • [32] Multi-objective planning of electrical distribution system using Imperialist Competitive Algorithm
    Zheng, Ying
    Yang, Yonggang
    Yu, Guangming
    ADVANCES IN ENERGY SCIENCE AND EQUIPMENT ENGINEERING, 2015, : 1823 - 1828
  • [33] A New Approach to Solve Multi-objective Transportation Problem
    Kaur, Lakhveer
    Rakshit, Madhuchanda
    Singh, Sandeep
    APPLICATIONS AND APPLIED MATHEMATICS-AN INTERNATIONAL JOURNAL, 2018, 13 (01): : 150 - 159
  • [34] On the Normalization in Evolutionary Multi-Modal Multi-Objective Optimization
    Liu, Yiping
    Ishibuchi, Hisao
    Yen, Gary G.
    Nojima, Yusuke
    Masuyama, Naoki
    Han, Yuyan
    2020 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2020,
  • [35] Multi-Objective Task Scheduling in Cloud Computing Using an Imperialist Competitive Algorithm
    Habibi, Majid
    Navimipour, Nima Jafari
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2016, 7 (05) : 289 - 293
  • [36] A New Multi-Objective Firework Algorithm to Solve the Multimodal Planning Network Problem
    Mnif, Mouna
    Bouamama, Sadok
    INTERNATIONAL JOURNAL OF APPLIED METAHEURISTIC COMPUTING, 2020, 11 (04) : 91 - 113
  • [37] A Modification of the Imperialist Competitive Algorithm with Hybrid Methods for Multi-Objective Optimization Problems
    Luo, Jianfu
    Zhou, Jinsheng
    Jiang, Xi
    Lv, Haodong
    SYMMETRY-BASEL, 2022, 14 (01):
  • [38] A multi-objective imperialist competitive algorithm (MOICA) for finding motifs in DNA sequences
    Gohardani, Saeed Alirezanejad
    Bagherian, Mehri
    Vaziri, Hamidreza
    MATHEMATICAL BIOSCIENCES AND ENGINEERING, 2019, 16 (03) : 1575 - 1596
  • [39] NSICA: Multi-objective imperialist competitive algorithm for feature selection in arrhythmia diagnosis
    Ayar, Mehdi
    Isazadeh, Ayaz
    Gharehchopogh, Farhad Soleimanian
    Seyedi, MirHojjat
    COMPUTERS IN BIOLOGY AND MEDICINE, 2023, 161
  • [40] A new optimization algorithm to solve multi-objective problems
    Sharifi, Mohammad Reza
    Akbarifard, Saeid
    Qaderi, Kourosh
    Madadi, Mohamad Reza
    SCIENTIFIC REPORTS, 2021, 11 (01)