Synopsis
A meta-heuristic is an iterative master process that guides and modifies the operations of subordinate heuristics to efficiently produce high-quality solutions, and recently, there have been significant advances in the theory and application of meta-heuristics to the approximate solutions of hard optimization problems. Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimization comprises a carefully refereed selection of extended versions of the best papers presented at the Second Meta-Heuristics Conference (MIC 97). The selected articles describe the most recent developments in theory and applications of meta-heuristics, heuristics for specific problems, and comparative case studies.
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