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What is Greedy Search

Chapter 14
Encyclopedia of Business Analytics and Optimization
Early generations of heuristics which improves the objective function value with each search move.
Published in Chapter:
Ant Colony Algorithm for Single Stage Supply Chain
R. Sridharan (National Institute of Technology Calicut, India) and Vinay V. Panicker (National Institute of Technology Calicut, India)
Copyright: © 2014 |Pages: 12
DOI: 10.4018/978-1-4666-5202-6.ch014
Abstract
Swarm intelligence has emerged as an approach for developing meta-heuristics to solve combinatorial optimization problems. Ant Colony Optimization (ACO) is an example for a swarm-intelligence based meta-heuristic inspired by the social behavior of colonies of ants. In this chapter, an ACO-based heuristic is proposed for solving a distribution-allocation problem in a single-stage of a supply chain. Thus, this work aims at modeling and analysis of the distribution-allocation problem in a single-stage supply chain with a fixed cost for a transportation route. In addition, it provides an insight for researchers in developing heuristics based on ant colony optimization for supply chain related problems.
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Chapter 130
Improving the Naïve Bayes Classifier
At each point in the search, the algorithm considers all local changes to the current set of attributes, makes its best selection, and never reconsiders this choice
Published in Chapter: Improving the Naïve Bayes Classifier; From: Encyclopedia of Artificial Intelligence
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