Solving the bi-objective multi-dimensional knapsack problem exploiting the concept of core

被引:13
|
作者
Mavrotas, George [1 ]
Figueira, Jose Rui [2 ]
Florios, Kostas [1 ]
机构
[1] Natl Tech Univ Athens, Athens 15780, Greece
[2] Univ Tecn Lisboa, Inst Super Tecn, Ctr Management Studies, Univ Paris 09,LAMSADE,CEG IST, P-2780990 Porto Salvo, Portugal
关键词
Knapsack; Multi-dimensional; Multi-objective programming; Core; ALGORITHM; EFFICIENT;
D O I
10.1016/j.amc.2009.08.045
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper deals with the bi-objective multi-dimensional knapsack problem. We propose the adaptation of the core concept that is effectively used in single-objective multi-dimensional knapsack problems. The main idea of the core concept is based on the "divide and conquer" principle. Namely, instead of solving one problem with n variables we solve several sub-problems with a fraction of n variables (core variables). The quality of the obtained solution can be adjusted according to the size of the core and there is always a trade off between the solution time and the quality of solution. In the specific study we de. ne the core problem for the multi-objective multi-dimensional knapsack problem. After de. ning the core we solve the bi-objective integer programming that comprises only the core variables using the Multicriteria Branch and Bound algorithm that can generate the complete Pareto set in small and medium size multi-objective integer programming problems. A small example is used to illustrate the method while computational and economy issues are also discussed. Computational experiments are also presented using available or appropriately modified benchmarks in order to examine the quality of Pareto set approximation with respect to the solution time. Extensions to the general multi-objective case as well as to the computation of the exact solution are also mentioned. (C) 2009 Elsevier Inc. All rights reserved.
引用
收藏
页码:2502 / 2514
页数:13
相关论文
共 50 条
  • [1] Using the idea of expanded core for the exact solution of bi-objective multi-dimensional knapsack problems
    Mavrotas, George
    Figueira, Jose Rui
    Antoniadis, Alexandros
    JOURNAL OF GLOBAL OPTIMIZATION, 2011, 49 (04) : 589 - 606
  • [2] Using the idea of expanded core for the exact solution of bi-objective multi-dimensional knapsack problems
    George Mavrotas
    José Rui Figueira
    Alexandros Antoniadis
    Journal of Global Optimization, 2011, 49 : 589 - 606
  • [3] A Dynamic Programming Algorithm for Solving Bi-Objective Fuzzy Knapsack Problem
    Singh, V. P.
    Chakraborty, D.
    MATHEMATICS AND COMPUTING, 2015, 139 : 289 - 306
  • [4] Solving the Multi-dimensional Multi-choice Knapsack Problem with the Help of Ants
    Iqbal, Shahrear
    Bari, Md Faizul
    Rahman, M. Sohel
    SWARM INTELLIGENCE, 2010, 6234 : 312 - 323
  • [5] An Analysis of Local Search for the Bi-objective Bidimensional Knapsack Problem
    Bezerra, Leonardo C. T.
    Lopez-Ibanez, Manuel
    Stutzle, Thomas
    EVOLUTIONARY COMPUTATION IN COMBINATORIAL OPTIMIZATION (EVOCOP 2013), 2013, 7832 : 85 - 96
  • [6] The bi-objective quadratic multiple knapsack problem: Model and heuristics
    Chen, Yuning
    Hao, Jin-Kao
    KNOWLEDGE-BASED SYSTEMS, 2016, 97 : 89 - 100
  • [7] Improved core problem based heuristics for the 0/1 multi-dimensional knapsack problem
    Della Croce, F.
    Grosso, A.
    COMPUTERS & OPERATIONS RESEARCH, 2012, 39 (01) : 27 - 31
  • [8] Automatic Generation of Multi-objective ACO Algorithms for the Bi-objective Knapsack
    Bezerra, Leonardo C. T
    Lopez-Ibanez, Manuel
    Stutzle, Thomas
    SWARM INTELLIGENCE (ANTS 2012), 2012, 7461 : 37 - 48
  • [9] Solving Bi-Objective Flow Shop Problem with Multi-Objective Path Relinking Algorithm
    Zeng, Rang-Qiang
    Shang, Ming-Sheng
    2014 10TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION (ICNC), 2014, : 343 - 348
  • [10] A reduction dynamic programming algorithm for the bi-objective integer knapsack problem
    Rong, Aiying
    Figueira, Jose Rui
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2013, 231 (02) : 299 - 313