Multi-objective meta-heuristics: An overview of the current state-of-the-art
European Journal of Operational ResearchPublished 1 February 2002
Dylan Jones, S.K. Mirrazavi, Mehrdad Tamiz
Citations564
SJR quartileQ1
SJR score2.24
SNIP2.62
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TL;DR
An overview of meta-heuristics methods utilized within the paradigm of multi-objective programming, which has undergone substantial expansion and development in the past decade is given.
Abstract
This paper gives an overview of meta-heuristics methods utilized within the paradigm of multi-objective programming. This is an area of research that has undergone substantial expansion and development in the past decade. A literature review for this period is presented and analyzed. Analysis of the types of multi-objective techniques and meta-heuristics is undertaken and reasons for their use hypothesized. The strengths and weaknesses of meta-heuristic methods as applied to multi-objective programmes are discussed. Finally, a summary is given together with suggestions for future research.
Keywords
Computer ScienceEngineering
Choice Reviews OnlineGenetic algorithms in search, optimization, and machine learning
49,278 Citations1989
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Multiple Criteria Optimization: Theory, Computation, and Application
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Modern heuristic techniques for combinatorial problems
2,623 Citations1993Colin R. Reeves
This chapter discusses combinatorial problems local and global optima heuristics, the tabu framework, and Evaluation of heuristic performance: analytical methods empirical testing statistical inference conclusions.
Management ScienceManagement Models and Industrial Applications of Linear Programming
1,899 Citations1957A. Charnes, W. W. Cooper
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1,227 Citations1998Carlos M. Fonseca, P.J. Fleming
The paper proposes that fitness assignment be interpreted as, or at least related to, a multicriterion decision process, and a suitable decision making framework based on goals and priorities is formulated in terms of a relational operator, characterized, and shown to encompass a number of simpler decision strategies.
Management ScienceA Class of Solutions for Group Decision Problems
1,095 Citations1973P. L. Yu
Given a set of utility functions defined on a decision space for a group of individuals, the concept of utopia point for the group as well as the group regret of a feasible decision is introduced.
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