scispace - formally typeset
Search or ask a question
Journal ArticleDOI

Dynamic optimization of chemical processes using ant colony framework.

01 Nov 2001-Computational Biology and Chemistry (Pergamon)-Vol. 25, Iss: 6, pp 583-595
TL;DR: Ant colony framework is illustrated by considering dynamic optimization of six important bench marking examples to illustrate its potential for solving a large class of process optimization problems in chemical engineering.
About: This article is published in Computational Biology and Chemistry.The article was published on 2001-11-01. It has received 88 citations till now. The article focuses on the topics: Metaheuristic & Ant colony optimization algorithms.
Citations
More filters
Journal ArticleDOI
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.

201 citations


Cites background from "Dynamic optimization of chemical pr..."

  • ...[29], Chunfeng and Xin [10] or Zhang et al....

    [...]

Journal ArticleDOI
TL;DR: An enhanced scatter search method for the global dynamic optimization of nonlinear processes using the control vector parametrization (CVP) approach is presented, providing a good balance between robustness and efficiency in the global phase, and couples a local search procedure to accelerate the convergence to optimal solutions.
Abstract: An enhanced scatter search method for the global dynamic optimization of nonlinear processes using the control vector parametrization (CVP) approach is presented. Sharing some features of the scatter search metaheuristic, this new method presents a simpler but more effective design which helps to overcome typical difficulties of nonlinear dynamic systems optimization such as noise, flat areas, nonsmoothness, and/or discontinuities. This new algorithm provides a good balance between robustness and efficiency in the global phase, and couples a local search procedure to accelerate the convergence to optimal solutions. Its application to four multimodal dynamic optimization problems, compared with other state-of-the-art global optimization algorithms, including an advanced scatter search design, proves its efficiency and robustness, showing a very good scalability.

118 citations

Journal ArticleDOI
TL;DR: This paper deals with the application and evaluation of a modified version of differential evolution called trigonometric differential evolution (TDE) algorithm for solving dynamic optimization problems encountered in chemical engineering which provides enhanced convergence speed.

101 citations

Journal ArticleDOI
TL;DR: In this article, a novel framework has been proposed for optimizing batch cooling crystallization operation, which can implement constrained multivariable optimization without the tendency of being trapped into local optima.

93 citations

Journal ArticleDOI
TL;DR: This paper reviews the theory and applications of ant algorithms, new methods of discrete optimization based on the simulation of self-organized colony of biologic ants, which are especially efficient for online optimization of processes in distributed nonstationary systems.
Abstract: This paper reviews the theory and applications of ant algorithms, new methods of discrete optimization based on the simulation of self-organized colony of biologic ants. The colony can be regarded as a multi-agent system where each agent is functioning independently by simple rules. Unlike the nearly primitive behavior of the agents, the behavior of the whole system happens to be amazingly reasonable. The ant algorithms have been extensively studied by European researchers from the mid-1990s. These algorithms have successfully been applied to solving many complex combinatorial optimization problems, such as the traveling salesman problem, the vehicle routing problem, the problem of graph coloring, the quadratic assignment problem, the problem of network-traffic optimization, the job-shop scheduling problem, etc. The ant algorithms are especially efficient for online optimization of processes in distributed nonstationary systems (for example, telecommunication network routing).

85 citations


Cites methods from "Dynamic optimization of chemical pr..."

  • ...The following applications of the ant systems should be emphasized: • in engineering, multiple objective design of water irrigation grids [25], optimization of water distribution [26], optimization of the GPS geodetic grids [27], optimization of the reliability with the help of redundancy [28], ergonomic design of computer keyboards [29], data allocation in memory of supercomputers [30], and dynamic optimization of chemical processes [ 31 ]; ......

    [...]

References
More filters
Journal ArticleDOI
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.
Abstract: This paper introduces the ant colony system (ACS), a distributed algorithm that is applied to the traveling salesman problem (TSP). In the ACS, a set of cooperating agents called ants cooperate to find good solutions to TSPs. Ants cooperate using an indirect form of communication mediated by a pheromone they deposit on the edges of the TSP graph while building solutions. We study the ACS by running experiments to understand its operation. The results show that the ACS outperforms other nature-inspired algorithms such as simulated annealing and evolutionary computation, and we conclude 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.

7,596 citations


"Dynamic optimization of chemical pr..." refers background in this paper

  • ...…applied to a variety of problems like, quadratic assignment problem (Maniezzo et al., 1994; Gambardella et al., 1999), travelling salesman problem (Dorigo and Gambardella, 1997), heat and power system optimization (Chou and Song, 1997), communication networks (Di Caro and Dorigo, 1998), batch…...

    [...]

Proceedings Article
01 Jan 1992
TL;DR: A distributed problem solving environment is introduced and its use to search for a solution to the travelling salesman problem is proposed.
Abstract: Ants colonies exhibit very interesting behaviours: even if a single ant only has simple capabilities, the behaviour of a whole ant colony is highly structured. This is the result of coordinated interactions. But, as communication possibilities among ants are very limited, interactions must be based on very simple flows of information. In this paper we explore the implications that the study of ants behaviour can have on problem solving and optimization. We introduce a distributed problem solving environment and propose its use to search for a solution to the travelling salesman problem.

2,826 citations

Journal ArticleDOI
TL;DR: AntNet is a distributed, mobile agents based Monte Carlo system that was inspired by recent work on the ant colony metaphor for solving optimization problems, and showed superior performance under all the experimental conditions with respect to its competitors.
Abstract: This paper introduces AntNet, a novel approach to the adaptive learning of routing tables in communications networks. AntNet is a distributed, mobile agents based Monte Carlo system that was inspired by recent work on the ant colony metaphor for solving optimization problems. AntNet's agents concurrently explore the network and exchange collected information. The communication among the agents is indirect and asynchronous, mediated by the network itself. This form of communication is typical of social insects and is called stigmergy. We compare our algorithm with six state-of-the-art routing algorithms coming from the telecommunications and machine learning fields. The algorithms' performance is evaluated over a set of realistic testbeds. We run many experiments over real and artificial IP datagram networks with increasing number of nodes and under several paradigmatic spatial and temporal traffic distributions. Results are very encouraging. AntNet showed superior performance under all the experimental conditions with respect to its competitors. We analyze the main characteristics of the algorithm and try to explain the reasons for its superiority.

1,712 citations


"Dynamic optimization of chemical pr..." refers background in this paper

  • ...…et al., 1999), travelling salesman problem (Dorigo and Gambardella, 1997), heat and power system optimization (Chou and Song, 1997), communication networks (Di Caro and Dorigo, 1998), batch scheduling problem (Jayaraman et al., 2000), continuous function optimization (Mathur et al., 2000) etc....

    [...]

Journal ArticleDOI
TL;DR: The aim is to provide a unified approach to the numerical solution of this general class of optimal control problems by using the control parametrization technique, where different types of constraints are shown to be equivalent to essentially the same functional form as the cost functional.

371 citations

Journal ArticleDOI
TL;DR: The use of orthogonal collocation is explored to reduce the dynamic optimization problem to an equality constrained nonlinear program (NLP) and the NLP is solved using a strategy that simultaneously converges and optimizes the algebraic model.

356 citations


"Dynamic optimization of chemical pr..." refers background in this paper

  • ...Biegler (1984) and Logsdon and Biegler (1989) have been very successful in applying collocation based nonlinear programming techniques for optimal design of some chemical systems....

    [...]