Journal ArticleDOI
Ant colony framework for optimal design and scheduling of batch plants
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TLDR
In this article, the ant colony optimisation paradigm is used for the optimal design of batch chemical processes and illustrates it by solving the combinatorial optimisation problem of multiproduct batch scheduling and the continuous function optimization problem for the design of multi-product plant with single product campaigns and horizon constraints.About:
This article is published in Computers & Chemical Engineering.The article was published on 2000-09-01. It has received 103 citations till now. The article focuses on the topics: Ant colony optimization algorithms & Job scheduler.read more
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Extended ant colony optimization for non-convex mixed integer nonlinear programming
TL;DR: Two novel extensions for the well known ant colony optimization (ACO) framework are introduced here, which allow the solution of mixed integer nonlinear programs (MINLPs) and a hybrid implementation based on this extended ACO framework, specially developed for complex non-convex MINLPs is presented.
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Improving food processing using modern optimization methods
TL;DR: In this contribution, computer-aided optimization is presented as the ultimate tool to improve food processing, especially focusing in recent developments using modern optimization techniques.
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Optimization of multi-pass turning operations using ant colony system
TL;DR: In this article, a new optimization technique based on the ant colony algorithm for solving multi-pass turning optimization problems is proposed, where the machining parameters are determined by minimizing the unit production cost, subject to various practical machining constraints.
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Optimization of Machining Parameters for Milling Operations Using Non-conventional Methods
TL;DR: In this paper, an optimization procedure based on the genetic algorithm, tabu search, ant colony algorithm and particle swarm optimization algorithm were developed for the optimization of machining parameters for milling operation.
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An ant colony optimization algorithm for the minimum weight vertex cover problem
TL;DR: A meta-heuristic based upon the Ant Colony Optimization (ACO) approach, to find approximate solutions to the minimum weight vertex cover problem, which incorporates several new features so as to select vertices out of the vertex set whereas the total weight can be minimized as much as possible.
References
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Proceedings Article
Distributed Optimization by Ant Colonies
TL;DR: A distributed problem solving environment is introduced and its use to search for a solution to the travelling salesman problem is proposed.
Book
Systematic Methods of Chemical Process Design
TL;DR: This chapter discusses the development of Optimization Theory and Methods for Process Design, and some of the techniques used in this work were new to the literature.
Journal ArticleDOI
Self-organized Shortcuts in the Argentine Ant
TL;DR: Les fourmis I. humilis choisissent le chemin le plus court pour aller de la colonie au lieu d'approvisionnement.
Journal ArticleDOI
The ant system applied to the quadratic assignment problem
TL;DR: A distributed heuristic algorithm that was inspired by the observation of the behavior of ant colonies is described and its use for the quadratic assignment problem is proposed.
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Trails and U-turns in the Selection of a Path by the Ant Lasius niger
TL;DR: The selection of the path is shown to be a collective process whereby trail laying and following amplifies small initial differences in the traffic on each path caused by these three mechanisms, and the foragers show no significant tendency to follow the path they used previously.