Multiagent cooperation for solving global optimization problems: an extendible framework with example cooperation strategies

This paper proposes the use of multiagent cooperation for solving global optimization problems through the introduction of a new multiagent environment, MANGO. The strength of the environment lays in its flexible structure based on communicating software agents that attempt to solve a problem cooper...

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Published in:Journal of global optimization 2013-10, Vol.57 (2), p.499-519
Main Authors: Aydemir, Fatma Başak, Günay, Akın, Öztoprak, Figen, Birbil, Ş. İlker, Yolum, Pınar
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Communication
Computer Science
Cooperation
Decision making
Flexible structures
Mathematical optimization
Mathematics
Mathematics and Statistics
Multiagent systems
Nonlinearity
Operations Research/Decision Theory
Optimization
Optimization algorithms
Problem solving
Real Functions
Roles
Run time (computers)
Software
Strategy
Studies
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cited_by cdi_FETCH-LOGICAL-c388t-4eb0b97f1dd1d31b64802c3b1e094dd21228351ac74e3b5d20e5aa7401b6188e3
cites cdi_FETCH-LOGICAL-c388t-4eb0b97f1dd1d31b64802c3b1e094dd21228351ac74e3b5d20e5aa7401b6188e3
container_end_page 519
container_issue 2
container_start_page 499
container_title Journal of global optimization
container_volume 57
creator Aydemir, Fatma Başak
Günay, Akın
Öztoprak, Figen
Birbil, Ş. İlker
Yolum, Pınar
description This paper proposes the use of multiagent cooperation for solving global optimization problems through the introduction of a new multiagent environment, MANGO. The strength of the environment lays in its flexible structure based on communicating software agents that attempt to solve a problem cooperatively. This structure allows the execution of a wide range of global optimization algorithms described as a set of interacting operations. At one extreme, MANGO welcomes an individual non-cooperating agent, which is basically the traditional way of solving a global optimization problem. At the other extreme, autonomous agents existing in the environment cooperate as they see fit during run time. We explain the development and communication tools provided in the environment as well as examples of agent realizations and cooperation scenarios. We also show how the multiagent structure is more effective than having a single nonlinear optimization algorithm with randomly selected initial points.
doi_str_mv 10.1007/s10898-012-0012-3
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subjects Algorithms
Analysis
Communication
Computer Science
Cooperation
Decision making
Flexible structures
Mathematical optimization
Mathematics
Mathematics and Statistics
Multiagent systems
Nonlinearity
Operations Research/Decision Theory
Optimization
Optimization algorithms
Problem solving
Real Functions
Roles
Run time (computers)
Software
Strategy
Studies
title Multiagent cooperation for solving global optimization problems: an extendible framework with example cooperation strategies
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