Adaptive memory programming for constrained global optimization

The problem of finding a global optimum of a constrained multimodal function has been the subject of intensive study in recent years. Several effective global optimization algorithms for constrained problems have been developed; among them, the multi-start procedures discussed in Ugray et al. [1] ar...

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Published inComputers & operations research Vol. 37; no. 8; pp. 1500 - 1509
Main Authors Lasdon, Leon, Duarte, Abraham, Glover, Fred, Laguna, Manuel, Martí, Rafael
Format Journal Article
LanguageEnglish
Published Kidlington Elsevier Ltd 01.08.2010
Elsevier
Pergamon Press Inc
Subjects
Applied sciences
Comparative analysis
Exact sciences and technology
Global optimization
Mathematical programming
Operational research and scientific management
Operational research. Management science
Optimization algorithms
Studies
Tabu search
Tabu search
Global optimization
Global optimum
Adaptive method
Constrained optimization
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Abstract The problem of finding a global optimum of a constrained multimodal function has been the subject of intensive study in recent years. Several effective global optimization algorithms for constrained problems have been developed; among them, the multi-start procedures discussed in Ugray et al. [1] are the most effective. We present some new multi-start methods based on the framework of adaptive memory programming (AMP), which involve memory structures that are superimposed on a local optimizer. Computational comparisons involving widely used gradient-based local solvers, such as Conopt and OQNLP, are performed on a testbed of 41 problems that have been used to calibrate the performance of such methods. Our tests indicate that the new AMP procedures are competitive with the best performing existing ones.
AbstractList The problem of finding a global optimum of a constrained multimodal function has been the subject of intensive study in recent years. Several effective global optimization algorithms for constrained problems have been developed; among them, the multi-start procedures discussed in Ugray et al. [1] are the most effective. We present some new multi-start methods based on the framework of adaptive memory programming (AMP), which involve memory structures that are superimposed on a local optimizer. Computational comparisons involving widely used gradient-based local solvers, such as Conopt and OQNLP, are performed on a testbed of 41 problems that have been used to calibrate the performance of such methods. Our tests indicate that the new AMP procedures are competitive with the best performing existing ones.
The problem of finding a global optimum of a constrained multimodal function has been the subject of intensive study in recent years. Several effective global optimization algorithms for constrained problems have been developed; among them, the multi-start procedures discussed in Ugray et al. are the most effective. We present some new multi-start methods based on the framework of adaptive memory programming (AMP), which involve memory structures that are superimposed on a local optimizer. Computational comparisons involving widely used gradient-based local solvers, such as Conopt and OQNLP, are performed on a testbed of 41 problems that have been used to calibrate the performance of such methods. Our tests indicate that the new AMP procedures are competitive with the best performing existing ones. [PUBLICATION ABSTRACT]
The problem of finding a global optimum of a constrained multimodal function has been the subject of intensive study in recent years. Several effective global optimization algorithms for constrained problems have been developed; among them, the multi-start procedures discussed in Ugray et al. [1] are the most effective. We present some new multi-start methods based on the framework of adaptive memory programming (AMP), which involve memory structures that are superimposed on a local optimizer. Computational comparisons involving widely used gradient-based local solvers, such as Conopt and OQNLP, are performed on a testbed of 41 problems that have been used to calibrate the performance of such methods. Our tests indicate that the new AMP procedures are competitive with the best performing existing ones.
Author Duarte, Abraham
Laguna, Manuel
Glover, Fred
Lasdon, Leon
Martí, Rafael
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Issue 8
Keywords Tabu search
Global optimization
Global optimum
Adaptive method
Constrained optimization
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Snippet The problem of finding a global optimum of a constrained multimodal function has been the subject of intensive study in recent years. Several effective global...
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SubjectTerms Applied sciences
Comparative analysis
Exact sciences and technology
Global optimization
Mathematical programming
Operational research and scientific management
Operational research. Management science
Optimization algorithms
Studies
Tabu search
Title Adaptive memory programming for constrained global optimization
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