Using the idea of expanded core for the exact solution of bi-objective multi-dimensional knapsack problems

We propose a methodology for obtaining the exact Pareto set of Bi-Objective Multi-Dimensional Knapsack Problems, exploiting the concept of core expansion. The core concept is effectively used in single objective multi-dimensional knapsack problems and it 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). In the multi-objective case, the general idea is that we start from an approximation of the Pareto set (produced with the Multi-Criteria Branch and Bound algorithm, using also the core concept) and we enrich this approximation iteratively. Every time an approximation is generated, we solve a series of appropriate single objective Integer Programming (IP) problems exploring the criterion space for possibly undiscovered, new Pareto Optimal Solutions (POS). If one or more new POS are found, we appropriately expand the already found cores and solve the new core problems. This process is repeated until no new POS are found from the IP problems. The paper includes an educational example and some experiments.

[1]  David Pisinger,et al.  Algorithms for Knapsack Problems , 1995 .

[2]  P. Pardalos,et al.  Pareto optimality, game theory and equilibria , 2008 .

[3]  Jacques Teghem,et al.  Two-phases Method and Branch and Bound Procedures to Solve the Bi–objective Knapsack Problem , 1998, J. Glob. Optim..

[4]  Hans Kellerer,et al.  Knapsack problems , 2004 .

[5]  José Rui Figueira,et al.  Solving the bi-objective multi-dimensional knapsack problem exploiting the concept of core , 2009, Appl. Math. Comput..

[6]  Egon Balas,et al.  An Algorithm for Large Zero-One Knapsack Problems , 1980, Oper. Res..

[7]  Shabnam Razavyan,et al.  The identification of nondominated and efficient paths on a network , 2005, Appl. Math. Comput..

[8]  S. Martello,et al.  Algorithms for Knapsack Problems , 1987 .

[9]  Ghasem Tohidi,et al.  A method for generating all efficient solutions of 0-1 multi-objective linear programming problem , 2005, Appl. Math. Comput..

[10]  George Mavrotas,et al.  Multi-criteria branch and bound: A vector maximization algorithm for Mixed 0-1 Multiple Objective Linear Programming , 2005, Appl. Math. Comput..

[11]  Carlos Gomes da Silva,et al.  An exact method for the bi-criteria { 0 , 1 }-knapsack problem based on functions specialization , 2005 .

[12]  George Mavrotas,et al.  A branch and bound algorithm for mixed zero-one multiple objective linear programming , 1998, Eur. J. Oper. Res..

[13]  David Kendrick,et al.  GAMS, a user's guide , 1988, SGNM.

[14]  Panos M. Pardalos,et al.  A survey of recent developments in multiobjective optimization , 2007, Ann. Oper. Res..

[15]  José Rui Figueira,et al.  Core problems in bi-criteria {0, 1}-knapsack problems , 2008, Comput. Oper. Res..

[16]  Arnaud Fréville,et al.  The multidimensional 0-1 knapsack problem: An overview , 2004, Eur. J. Oper. Res..

[17]  Marco Laumanns,et al.  An efficient, adaptive parameter variation scheme for metaheuristics based on the epsilon-constraint method , 2006, Eur. J. Oper. Res..

[18]  Günther R. Raidl,et al.  The Core Concept for the Multidimensional Knapsack Problem , 2006, EvoCOP.

[19]  S. Martello,et al.  A New Algorithm for the 0-1 Knapsack Problem , 1988 .

[20]  John E. Beasley,et al.  A Genetic Algorithm for the Multidimensional Knapsack Problem , 1998, J. Heuristics.

[21]  Marc Despontin,et al.  Multiple Criteria Optimization: Theory, Computation, and Application, Ralph E. Steuer (Ed.). Wiley, Palo Alto, CA (1986) , 1987 .

[22]  Heather Fry,et al.  A user’s guide , 2003 .

[23]  José Rui Figueira,et al.  A Scatter Search Method for the Bi-Criteria Multi-dimensional {0,1}-Knapsack Problem using Surrogate Relaxation , 2004, J. Math. Model. Algorithms.

[24]  Paolo Toth,et al.  Knapsack Problems: Algorithms and Computer Implementations , 1990 .

[25]  Fariborz Jolai,et al.  Exact algorithm for bi-objective 0-1 knapsack problem , 2007, Appl. Math. Comput..