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The solution of singular optimal control problems using the modified line-up competition algorithm with region-relaxing strategy

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ISA TRANSACTIONS 2010年第1期49卷 106-113页

作者： Sun, Daim-Yuang Natl Chin Yi Univ Technol Dept Chem & Mat Engn Taichung 411 Taiwan

In this study, singular optimal control problems are solved by line-up competition algorithm (LCA) under the framework of control parametrization. Two steps that promote the convergence quality of LCA are taken. One is to use normal (Gaussian) sampling policy to replace uniform sampling policy to accelerate initial convergence, while the other is to introduce region-relaxing strategy to enhance the refinement of solutions in final convergence. Four typical examples are given to illustrate the proposed algorithm. The results show that such modifications make LCA more robust and efficient in the solutions of singular optimal control problems. (C) 2009 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： Singular optimal control line-up competition algorithm Control vector parametrization Region-relaxing strategy

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Solving mixed integer nonlinear programming problems with line-up competition algorithm

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COMPUTERS & CHEMICAL ENGINEERING 2004年第12期28卷 2647-2657页

作者： Yan, LX Shen, K Hu, SH Wuhan Univ Technol Dept Chem Engn Wuhan 430070 Peoples R China

line-up competition algorithm (LCA), a global optimization algorithm proposed recently, is applied to the solution of mixed integer nonlinear programming (MINLP) problems. Through using alternative schemes to handle integer variables, the algorithm reported previously for solving NLP problems can be extended expediently to the solution of MINLP problems. The performance of the LCA is tested with several non-convex MINLP problems published in the literature, including the optimal design of multi-product batch chemical processes and the location-allocation problem. Testing shows that the LCA algorithm is efficient and robust in the solution of MINLP problems. (C) 2004 Elsevier Ltd. All rights reserved.

关键词： line-up competition algorithm global optimization mixed integer nonlinear programming multi-product batch chemical processes location-allocation problem

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The solutions of time-delayed optimal control problems by the use of modified line-up competition algorithm

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JOURNAL OF THE TAIWAN INSTITUTE OF CHEMICAL ENGINEERS 2010年第1期41卷 54-64页

作者： Sun, Daim-Yuang Huang, Tzu-Chen Natl Chin Yi Univ Technol Dept Chem & Mat Engn Taichung 411 Taiwan

In this article, line-up competition algorithm (LCA), a brand-new nonlinear programming method based on the principle of evolution, is applied to solve time-delay optimal control problems (TDOCPs). The problems are first discretized based on the concept of control vector parametrization, and then solved by LCA. Since the delay differential equations are directly integrated without using the auxiliary procedures Such as model conversion and data interpolation, most TDOCPs can be solved very conveniently under such solution framework. Meanwhile, a more efficient sampling strategy is adopted to promote the too slow convergence of the basic LCA. By solving six typical examples, including five pure mathematical problems and one chemical engineering problem, the modified LCA demonstrates a robust and efficient property in optimizing time-delay unsteady systems. (C) 2009 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

关键词： Time Delay Optimal control problems Evolutionary algorithms line-up competition algorithm Nonlinear programming

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Global optimization of non-convex nonlinear programs using line-up competition algorithm

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COMPUTERS & CHEMICAL ENGINEERING 2001年第11-12期25卷 1601-1610页

作者： Yan, LX Ma, DX Hubei Polytech Univ Dept Chem Engn Wuhan 430068 Peoples R China Beijing Inst Chem Technol Dept Comp Sci Beijing 100029 Peoples R China

A global optimization algorithm of simulating evolutionary process, called line-up competition algorithm (LCA), was recently proposed. In the LCA, all families are independent and parallel during evolution. According to the value of their objective function, all families are ranked a line-up and are allocated different search spaces based on their positions in the line-up. The preceding excellent families in the line-up gain less search space, which is favorable for local search, accelerating to find optimal point, while the latter worse families gain larger search space, which is helpful for global search. Through the competition of two levels of inside a family and between families, the first family in the line-up is continually replaced by other families, or the value of objective function of the first family is updated continually. As a result, the optimal solution is approached rapidly. In this paper, the superior performances of the LCA were demonstrated in detail by solving some difficult non-convex nonlinear programming problems constrained and unconstrained. (C) 2001 Elsevier Science Ltd. All rights reserved.

关键词： line-up competition algorithm global optimization evolutionary algorithm nonlinear programming

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Solving combinatorial optimization problems with line-up competition algorithm

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COMPUTERS & CHEMICAL ENGINEERING 2003年第2期27卷 251-258页

作者： Yan, LX Wuhan Univ Technol Dept Chem Engn Wuhan 430070 Peoples R China

The line-up competition algorithm (LCA), a simulated evolutionary algorithm, is proposed for solving combinatorial optimization problems. In the LCA, there exist independent and parallel families during evolution. Two means of competitions, the competitions between families and inside a family, are used to increase the search efficiency. Again, all families are ranked a line-up based on their objective function, and allocated different search spaces according to their position in the line-up, which is favorable to balance local and global search. The LCA algorithm is applied to the solution of knapsack problem and the optimal design of pressure relief header network. Computational results reveal that the LCA algorithm is able to find optimal or near-optimal solutions after examining an extremely small fraction of search space. (C) 2002 Elsevier Science Ltd. All rights reserved.

关键词： line-up competition algorithm evolutionary algorithm combinatorial optimization knapsack problem pipe network

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Multi-period Optimal Operational Planning of Boiler Steam System Based on line-up competition algorithm

Multi-period Optimal Operational Planning of Boiler Steam Sy...

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2nd International Conference on Advances in Energy Engineering (ICAEE)

作者： Chen, Guohui Shi, Bin Yan, Liexiang Wuhan Univ Technol Sch Mech & Elect Engn Wuhan 430070 Peoples R China Wuhan Univ Technol Sch Chem Engn Wuhan 430070 Peoples R China

In this paper, a multi-period mixed integer nonlinear programming (MINLP) model for boiler steam system, which accounts for both the operating cost for each period and the changeover cost each between periods of operation, is presented. To find an exact solution for the MINLP problem within an allowable computation time, a new hybrid algorithm combining the line-up competition algorithm (LCA) with nonlinear programming is proposed. A boiler steam system contains six boilers is used for case study. And the results show a significant potential for cost saving. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the organizing committee of 2nd International Conference on Advances in Energy Engineering (ICAEE).

关键词： Boiler steam system Optimization line-up competition algorithm MINLP

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Application of line-up competition algorithm with Variable Weight for Tree Pipe Network Layout Optimization

Application of Line-up Competition Algorithm with Variable W...

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International Conference on Electrical Information and Mechatronics (ICEIM)

作者： Fu, Yujuan Zhang, Yulong Cai, Huanjie He, Junshi Kang, Yinhong Shenyang Agr Univ Key Lab Agr Resource & Environm Liaoning Prov Shenyang 110866 Peoples R China Northwest A&F Univ Key Lab Agr Soil & Water Yangling Shaanxi 712100 Peoples R China Shenyang Agr Univ Coll water resource Shenyang 110866 Liaoning Peoples R China Sichuan Agr Univ Dept Informat & Engn Technol Yaan 625014 Peoples R China

ISBN: (纸本)9783037853115

As a problem of network flows, pipe network layout optimization is a combinatorial problem with variable weight. This paper takes flow variation by different layout scheme into account to the pipeline optimization and obtains the irrigation pipe network layout optimization with variable weight. line-up competition algorithm (LCA) is introduced to optimize the tree pipe network layout. The corresponding fitness function, encoded mode and mutation are designed on the basis of the characteristic of tree graph expressed by adjacency matrix. It is testified by case study that LCA can obtain the optimal result, and is better in search efficiency and much stable compared with other algorithms.

关键词： tree pipe network layout optimization variable weight line-up competition algorithm

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Multi-period Optimal Operational Planning of Boiler Steam System Based on line-up competition algorithm

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Energy Procedia 2012年 14卷 613-619页

作者： Guohui Chen Bin Shi Liexiang Yan School of Mechanical and Electronic Engineering Wuhan University of Technology Wuhan 430070 China School of Chemical Engineering Wuhan University of Technology Wuhan 430070 China

关键词： Boiler steam system Optimization line-up competition algorithm MINLP

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Solving location-allocation problem with line-up competition algorithm

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Wuhan Ligong Daxue Xuebao/Journal of Wuhan University of Technology 2005年第12期27卷 105-107页

作者： Shen, Kun Shi, Bin Yan, Lie-Xiang School of Materials Science and Engineering Wuhan University of Technology Wuhan 430070 China

Location-allocation problems are attributed to mixed integer nonlinear program problems. In order to use line-up competition algorithm (LCA) to solve these problems, a strategy was proposed for handing parallel integer and continuous variables, which could reach the balance between global search and local search. LCA was applied to solve a larger scale location-allocation problem, and the solutions obtained were superior to those obtained by a hybrid algorithm of coupling genetic algorithm and grid search method in the literature. The result indicates that the LCA is efficient and robust for solving difficult global optimization problems.

关键词： Globe optimization line-up competition algorithm Location-allocation problem Mixed integer nonlinear program

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A new multi-objective evolutionary algorithm: neighbourhood exploring evolution strategy

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ENGINEERING OPTIMIZATION 2005年第4期37卷 351-379页

作者： Hu, XL Coello, CAC Huang, ZC IPN CINVESTAV Mexico City 07300 DF Mexico Wuhan Univ Technol Automot Engn Inst Wuhan 430070 Peoples R China Wuhan Univ Technol Sch Sci Wuhan 430070 Peoples R China

This article proposes a new multi-objective evolutionary algorithm, called neighbourhood exploring evolution strategy (NEES). This approach incorporates the idea of neighbourhood exploration together with other techniques commonly used in the multi-objective evolutionary optimization literature (namely, non-dominated sorting and diversity preservation mechanisms). The main idea of the proposed approach was derived from a single-objective evolutionary algorithm, called the line-up competition algorithm (LCA), and it consists of assigning neighbourhoods of different sizes to different solutions. Within each neighbourhood, new solutions are generated using a (1 + lambda)-ES (evolution strategy). This scheme naturally balances the effect of local search (which is performed by the neighbourhood exploration mechanism) with that of the global search performed by the algorithm, and gradually impels the population to progress towards the true Pareto-optimal front of the problem to explore the extent of that front. Three versions of the proposal are studied: a (1 + 1)-NEES, a (1 + 2)-NEES and a (1 + 4)-NEES. Such approaches are validated on a set of standard test problems reported in the specialized literature. Simulation results indicate that, for continuous numerical optimization problems, the proposal (particularly the (1 + 1)-NEES) is competitive with respect to NSGA-II, which is an algorithm representative of the state-of-the-art in evolutionary multi-objective optimization. Moreover, all the versions of NEES improve on the results of NSGA-II when dealing with a discrete optimization problem. Although preliminary, such results might indicate a potential application area in which the proposed approach could be particularly useful.

关键词： neighbourhood exploring evolution strategy line-up competition algorithm multi-objective optimization evolutionary algorithm evolution strategy

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