Journal ArticleDOI
Ant colony framework for optimal design and scheduling of batch plants
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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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Journal ArticleDOI
Iterative ant-colony algorithm and its application to dynamic optimization of chemical process
TL;DR: IACA approach can be regarded as a reliable and useful optimization tool when gradient is not available and gradually approximate the optimal control profile.
Journal ArticleDOI
Sensitivity-based conceptual design and tolerance allocation using the continuous ants colony algorithm (CACO)
TL;DR: In this article, the continuous ants colony algorithm is used as an optimization tool for minimizing the critical dimension deviation and allocating the cost-based optimal tolerances for the corresponding dimensions.
Journal ArticleDOI
Ants colony algorithm approach for multi-objective optimisation of surface grinding operations
TL;DR: In this paper, an ant colony based optimization procedure was developed to optimise grinding conditions, viz. wheel speed, workpiece speed, depth of dressing and lead of dressing, using a multi-objective function model with a weighted approach for the surface grinding process.
Journal ArticleDOI
A Comprehensive Overview of the Applications of Artificial Life
Kyung-Joong Kim,Sung-Bae Cho +1 more
TL;DR: The applications of artificial life (ALife), the creation of synthetic life on computers to study, simulate, and understand living systems, are reviewed.
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An ant colony classifier system: application to some process engineering problems
TL;DR: The results indicate that the ant classifier is able to discover rules in the data sets with better predictive accuracy than the C4.5 algorithm.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Genetic algorithms in search, optimization and machine learning
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Journal ArticleDOI
Ant system: optimization by a colony of cooperating agents
TL;DR: It is shown how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling, and the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.
Journal ArticleDOI
Ant colony system: a cooperative learning approach to the traveling salesman problem
TL;DR: The results show that the ACS outperforms other nature-inspired algorithms such as simulated annealing and evolutionary computation, and it is concluded comparing ACS-3-opt, a version of the ACS augmented with a local search procedure, to some of the best performing algorithms for symmetric and asymmetric TSPs.