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
  • [31] Optimising the bi-objective multidimensional integer knapsack problem using non-dominated sorting particle swarm optimisation
    Bagherinejad J.
    Dehghani M.
    International Journal of Industrial and Systems Engineering, 2016, 23 (03) : 263 - 289
  • [32] On solving bi-objective constrained minimum spanning tree problems
    Carvalho, Iago A.
    Coco, Amadeu A.
    JOURNAL OF GLOBAL OPTIMIZATION, 2023, 87 (01) : 301 - 323
  • [33] A bi-objective model for the retail spatial design problem
    Yapicioglu, Haluk
    Smith, Alice E.
    ENGINEERING OPTIMIZATION, 2012, 44 (03) : 243 - 266
  • [34] Bi-Objective version of Team Orienteering Problem (BTOP)
    HajMirzaei, Milad
    Ziarati, Koorush
    Naghibi, Mohammad-Taghi
    PROCEEDINGS OF THE 2017 7TH INTERNATIONAL CONFERENCE ON COMPUTER AND KNOWLEDGE ENGINEERING (ICCKE), 2017, : 1 - 7
  • [35] A Bi-Objective Formulation For Refueling Stations Selection Problem
    Ferdowsi, F.
    Maleki, H. R.
    Rivaz, S.
    JOURNAL OF MATHEMATICAL EXTENSION, 2019, 13 (03) : 71 - 85
  • [36] A two-phase Pareto front method for solving the bi-objective personnel task rescheduling problem
    Borgonjon, Tessa
    Maenhout, Broos
    COMPUTERS & OPERATIONS RESEARCH, 2022, 138
  • [37] A Two-Stage ε-Constraint Strategy-Based Heuristic for Bi-Objective Quadratic Multiple Knapsack Problems
    Aider, Meziane
    Gacem, Oussama
    Hifi, Mhand
    2020 7TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING & MACHINE INTELLIGENCE (ISCMI 2020), 2020, : 51 - 55
  • [38] Construct, Merge, Solve and Adapt Versus Large Neighborhood Search for Solving the Multi-dimensional Knapsack Problem: Which One Works Better When?
    Lizarraga, Evelia
    Blesa, Maria J.
    Blum, Christian
    EVOLUTIONARY COMPUTATION IN COMBINATORIAL OPTIMIZATION (EVOCOP 2017), 2017, 10197 : 60 - 74
  • [39] Multi-Objective Factored Evolutionary Optimization and the Multi-Objective Knapsack Problem
    Peerlinck, Amy
    Sheppard, John
    2022 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2022,
  • [40] Grey Wolf Optimizer with Multi Step Crossover for Bi-objective Job Shop Scheduling Problem
    Gunadiz, Safia
    Berrichi, Ali
    ADVANCES IN COMPUTING SYSTEMS AND APPLICATIONS, 2022, 513 : 261 - 272