A Probability Collectives Approach with a Feasibility-Based Rule for Constrained Optimization

Joint Authors

Tai, K.
Kulkarni, Anand J.

Source

Applied Computational Intelligence and Soft Computing

Issue

Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-19, 19 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2011-12-20

Country of Publication

Egypt

No. of Pages

19

Main Subjects

Information Technology and Computer Science

Abstract EN

This paper demonstrates an attempt to incorporate a simple and generic constraint handling technique to the Probability Collectives (PC) approach for solving constrained optimization problems.

The approach of PC optimizes any complex system by decomposing it into smaller subsystems and further treats them in a distributed and decentralized way.

These subsystems can be viewed as a Multi-Agent System with rational and self-interested agents optimizing their local goals.

However, as there is no inherent constraint handling capability in the PC approach, a real challenge is to take into account constraints and at the same time make the agents work collectively avoiding the tragedy of commons to optimize the global/system objective.

At the core of the PC optimization methodology are the concepts of Deterministic Annealing in Statistical Physics, Game Theory and Nash Equilibrium.

Moreover, a rule-based procedure is incorporated to handle solutions based on the number of constraints violated and drive the convergence towards feasibility.

Two specially developed cases of the Circle Packing Problem with known solutions are solved and the true optimum results are obtained at reasonable computational costs.

The proposed algorithm is shown to be sufficiently robust, and strengths and weaknesses of the methodology are also discussed.

American Psychological Association (APA)

Kulkarni, Anand J.& Tai, K.. 2011. A Probability Collectives Approach with a Feasibility-Based Rule for Constrained Optimization. Applied Computational Intelligence and Soft Computing،Vol. 2011, no. 2011, pp.1-19.
https://search.emarefa.net/detail/BIM-513172

Modern Language Association (MLA)

Kulkarni, Anand J.& Tai, K.. A Probability Collectives Approach with a Feasibility-Based Rule for Constrained Optimization. Applied Computational Intelligence and Soft Computing No. 2011 (2011), pp.1-19.
https://search.emarefa.net/detail/BIM-513172

American Medical Association (AMA)

Kulkarni, Anand J.& Tai, K.. A Probability Collectives Approach with a Feasibility-Based Rule for Constrained Optimization. Applied Computational Intelligence and Soft Computing. 2011. Vol. 2011, no. 2011, pp.1-19.
https://search.emarefa.net/detail/BIM-513172

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-513172