Title

An Investigation Of The Relationship Between Problem Characteristics And Algorithm Performance: A Case Study Of The Gap

Abstract

We compare synthetic Generalized Assignment Problems (GAP) generated under two correlation-induction strategics: Implicit Correlation Induction (ICI) and Explicit Correlation Induction (ECI). We present computational results for two commercially-available solvers and four heuristics on 590 test problems. We conclude that the solvers’ performances degrade as the population correlation between the objective function and capacity constraint coefficients decreases. However, the heuristics’ performances improved as the absolute value of the same population correlation increases. We find that problems generated under ECI arc more challenging than problems generated under ICI and may lead to a better understanding of the capabilities and limitations of the solution methods being evaluated. We recommend that one consider the purpose(s) of an experiment and types of solution procedures to be evaluated when determining what types of test problems to generate. © 2002, Taylor & Francis Group, LLC.

Publication Date

1-1-2002

Publication Title

IIE Transactions (Institute of Industrial Engineers)

Volume

34

Issue

3

Number of Pages

297-312

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1080/07408170208928871

Socpus ID

85023897336 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85023897336

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