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Integrated Supply Chain Optimization Model Using Mixed Integer Linear Programming

100%
Sitek P., Wikarek J.
Logistics and Transport
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2013
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vol. 20
37-48
EN
This article presents an integrated approach to optimize the different functions in a supply chain on strategic tactical and operational levels. The integrated supply chain model has been formulated as a cost minimization problem in the form of MILP (Mixed Integer Linear Programming). The costs of production, transport, distribution and environmental protection were adopted as optimization criteria. Timing, volume, capacity and mode of transport were also taken into account. The model was implemented in the LINGO package. The implementation model and the numerical tests are presented and discussed. The numerical experiments were carried out using sample data to show the possibilities of practical decision support and optimization of the supply chain.
2
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Perturbation algorithm for a minimax regret minimum spanning tree problem

100%
MAKUCHOWSKI M.
Operations Research and Decisions
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2014
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vol. 24
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issue 1
37-49
EN
The problem of finding a robust spanning tree has been analysed. The problem consists of determining a minimum spanning tree of a graph with uncertain edge costs. We should determine a spanning tree that minimizes the difference in costs between the tree selected and the optimal tree. While doing this, all possible realizations of the edge costs should be taken into account. This issue belongs to the class of NP-hard problems. In this paper, an algorithm based on the cost perturbation method and adapted to the analysed problem has been proposed. The paper also contains the results of numerical experiments testing the effectiveness of the proposed algorithm and compares it with algorithms known in the literature. The research is based on a large number of various test examples taken from the literature.
3
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A computational study of approximation algorithms for a minmax resource allocation problem

100%
PRZYBYSŁAWSKI B., KASPERSKI A.
Operations Research and Decisions
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2012
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vol. 22
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issue 2
35-43
EN
A basic resource allocation problem with uncertain costs has been discussed. The problem is to minimize the total cost of choosing exactly p items out of n available. The uncertain item costs are specified as a discrete scenario set and the minmax criterion is used to choose a solution. This problem is known to be NP-hard, but several approximation algorithms exist. The aim of this paper is to investigate the quality of the solutions returned by these approximation algorithms. According to the results obtained, the randomized algorithms described are fast and output solutions of good quality, even if the problem size is large.
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