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The Minmax Multidimensional Knapsack Problem with Application to a Chance-Constrained Problem

The Minmax Multidimensional Knapsack Problem with Application to a Chance-Constrained Problem
The Minmax Multidimensional Knapsack Problem with Application to a Chance-Constrained Problem
In this paper we present a new combinatorial problem, called minmax multidimensional knapsack problem (MKP), motivated by a military logistics problem. The logistics problem is a two-period, two-level, chanced-constrained problem with recourse. We show that the MKP is NP-hard and develop a practically efficient combinatorial algorithm for solving it. We also show that under some reasonable assumptions regarding the operational setting of the logistics problem, the chance-constrained optimization problem is decomposable into a series of MKPs that are solved separately.
656-666
Kress, Moshe
394ef728-d925-4ca5-8c0e-d3f18b1f8a31
Penn, Michal
4b303716-075a-4f19-8889-a45120885942
Polukarov, Maria
bd2f0623-9e8a-465f-8b29-851387a64740
Kress, Moshe
394ef728-d925-4ca5-8c0e-d3f18b1f8a31
Penn, Michal
4b303716-075a-4f19-8889-a45120885942
Polukarov, Maria
bd2f0623-9e8a-465f-8b29-851387a64740

Kress, Moshe, Penn, Michal and Polukarov, Maria (2007) The Minmax Multidimensional Knapsack Problem with Application to a Chance-Constrained Problem. Naval Research Logistics, 54 (6), 656-666.

Record type: Article

Abstract

In this paper we present a new combinatorial problem, called minmax multidimensional knapsack problem (MKP), motivated by a military logistics problem. The logistics problem is a two-period, two-level, chanced-constrained problem with recourse. We show that the MKP is NP-hard and develop a practically efficient combinatorial algorithm for solving it. We also show that under some reasonable assumptions regarding the operational setting of the logistics problem, the chance-constrained optimization problem is decomposable into a series of MKPs that are solved separately.

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Published date: 2007
Organisations: Agents, Interactions & Complexity

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Local EPrints ID: 267886
URI: http://eprints.soton.ac.uk/id/eprint/267886
PURE UUID: 291b2532-6036-4d3c-8ceb-6723a10b734c

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Date deposited: 16 Sep 2009 20:44
Last modified: 14 Mar 2024 09:01

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Contributors

Author: Moshe Kress
Author: Michal Penn
Author: Maria Polukarov

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