JOURNAL ARTICLE

A min-max resource allocation problem with substitutions

Jong‐Shi PangChang-Sung Yu

Year: 1989 Journal:   European Journal of Operational Research Vol: 41 (2)Pages: 218-223   Publisher: Elsevier BV

Abstract

In this paper, a model for a resource allocation problem with substitution is presented. The model extends a previous one proposed by Luss and Smith for resource allocation without substitutions. In general, two resources are substitutable if they can be used in place of one another in the allocation process. If two resources are substitutable for the same set of activities, then they can be combinaed into and treated as a single resource; otherwise, substitution needs to be dealt with explicitly. One application of the resource allocation problem with substitutions arises from the assembly of electronic components onto circuit boards. Typically, several components can be assembled in the same locations of a board, they then become substitutes of one another. The problem here is to determine how much to produce of the circuit boards and how to efficiently allocate the components so as to minimize the maximum weighted deviation from target demands of the boards. It is explained how the proposed model can be solved by a parametric transportation algorithm, present some computational results and discuss a nonlinear extension.

Keywords:
Substitution (logic) Resource allocation Computer science Mathematical optimization Parametric programming Parametric statistics Extension (predicate logic) Set (abstract data type) Process (computing) Resource (disambiguation) Nonlinear system Operations research Mathematics

Metrics

35
Cited By
2.10
FWCI (Field Weighted Citation Impact)
11
Refs
0.88
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Optimization and Packing Problems
Physical Sciences →  Engineering →  Industrial and Manufacturing Engineering
Operations Management Techniques
Social Sciences →  Decision Sciences →  Management Science and Operations Research
Advanced Manufacturing and Logistics Optimization
Physical Sciences →  Engineering →  Industrial and Manufacturing Engineering

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