State transition algorithm for constrained optimization problems
- Authors: Han, Jie , Dong, Tianxue , Zhou, Xiaojun , Yang, Chunhua , Gui, Weihua
- Date: 2014
- Type: Text , Conference proceedings
- Full Text: false
- Description: In this study, a population-based continuous state transition algorithm (STA) is investigated into continuous constrained optimization problems. After an analysis of the advantages and disadvantages of two well-known constraint-handling techniques, penalty function method and feasibility preference method, a two-stage strategy is proposed for constrained STA, in which, the feasibility preference method is adopted in the early stage of an iteration process whilst it is changed to the penalty function method in the later stage. Several benchmark tests are given to evaluate the performance of the proposed method, and the experimental results show that the constrained STA with a two-stage strategy outperforms other single strategy in terms of both global search ability and solution precision.
A comparative study of state transition algorithm with harmony search and artificial bee colony
- Authors: Zhou, Xiaojun , Gao, David , Yang, Chunhua
- Date: 2013
- Type: Text , Journal article
- Relation: Advances in Intelligent Systems and Computing Vol. 212, no. (2013), p. 651-659
- Full Text: false
- Reviewed:
- Description: We focus on a comparative study of three recently developed nature-inspired optimization algorithms, including state transition algorithm, harmony search and artificial bee colony. Their core mechanisms are introduced and their similarities and differences are described. Then, a suit of 27 well-known benchmark problems are used to investigate the performance of these algorithms and finally we discuss their general applicability with respect to the structure of optimization problems. © Springer-Verlag Berlin Heidelberg 2013.
- Description: 2003011220
State transition algorithm for traveling salesman problem
- Authors: Yang, Chunhua , Tang, Xiaolin , Zhou, Xiaojun , Gui, Weihua
- Date: 2012
- Type: Text , Conference proceedings
- Full Text:
- Description: Discrete version of state transition algorithm is proposed in order to solve the traveling salesman problem. Three special operators for discrete optimization problem named swap, shift and symmetry transformations are presented. Convergence analysis and time complexity of the algorithm are also considered. To make the algorithm simple and efficient, no parameter adjusting is suggested in current version. Experiments are carried out to test the performance of the strategy, and comparisons with simulated annealing and ant colony optimization have demonstrated the effectiveness of the proposed algorithm. The results also show that the discrete state transition algorithm consumes much less time and has better search ability than its counterparts, which indicates that state transition algorithm is with strong adaptability. © 2012 Chinese Assoc of Automati.
A discrete state transition algorithm for traveling salesman problem
- Authors: Yang, Chunhua , Tang, Xiaolin , Zhou, Xiaojun , Gui, Weihua
- Date: 2013
- Type: Text , Journal article
- Relation: Kongzhi Lilun Yu Yingyong/Control Theory and Applications Vol. 30, no. 8 (2013), p. 1040-1046
- Full Text: false
- Reviewed:
- Description: A discrete version of state transition algorithm is proposed to solve the traveling salesman problem. Three special operators named swap, shift and symmetry transformations are presented for discrete optimization problem. Convergence analysis and time complexity of the algorithm are also considered. To make the algorithm efficient, a parametric study is investigated. Experiments are carried out to test its performance, and comparisons with simulated annealing and ant colony optimization have demonstrated the effectiveness of the proposed algorithm. The results also show that the discrete state transition algorithm consumes much less time and has better search ability than other traditional combinatorial optimization methods, indicating that state transition algorithm has strong adaptability.
- Description: C1
A BMI approach to guaranteed cost control of discrete-time uncertain system with both state and input delays
- Authors: Zhou, Xiaojun , Dong, Tianxue , Tang, Xiaolin , Yang, Chunhua , Gui, Weihua
- Date: 2015
- Type: Text , Journal article
- Relation: Optimal Control Applications and Methods Vol. 36, no. 6 (2015), p. 844-852
- Full Text: false
- Reviewed:
- Description: In this study, the guaranteed cost control of discrete time uncertain system with both state and input delays is considered. Sufficient conditions for the existence of a memoryless state feedback guaranteed cost control law are given in the bilinear matrix inequality form, which needs much less auxiliary matrix variables and storage space. Furthermore, the design of guaranteed cost controller is reformulated as an optimization problem with a linear objective function, bilinear, and linear matrix inequalities constraints. A nonlinear semi-definite optimization solver - PENLAB is used as a solution technique. A numerical example is given to demonstrate the effectiveness of the proposed method. Copyright © 2014 John Wiley & Sons, Ltd.
Discrete state transition algorithm for unconstrained integer optimization problems
- Authors: Zhou, Xiaojun , Gao, David , Yang, Chunhua , Gui, Weihua
- Date: 2016
- Type: Text , Journal article
- Relation: Neurocomputing Vol. 173, no. (2016), p. 864-874
- Full Text:
- Reviewed:
- Description: A recently new intelligent optimization algorithm called discrete state transition algorithm is considered in this study, for solving unconstrained integer optimization problems. Firstly, some key elements for discrete state transition algorithm are summarized to guide its well development. Several intelligent operators are designed for local exploitation and global exploration. Then, a dynamic adjustment strategy "risk and restoration in probability" is proposed to capture global solutions with high probability. Finally, numerical experiments are carried out to test the performance of the proposed algorithm compared with other heuristics, and they show that the similar intelligent operators can be applied to ranging from traveling salesman problem, boolean integer programming, to discrete value selection problem, which indicates the adaptability and flexibility of the proposed intelligent elements. (C) 2015 Elsevier B.V. All rights reserved.
Canonical primal-dual algorithm for solving fourth-order polynomial minimization problems
- Authors: Zhou, Xiaojun , Gao, David , Yang, Chunhua
- Date: 2014
- Type: Text , Journal article
- Relation: Applied Mathematics and Computation Vol. 227, no. (2014), p. 246-255
- Full Text: false
- Reviewed:
- Description: This paper focuses on implementation of a general canonical primal-dual algorithm for solving a class of fourth-order polynomial minimization problems. A critical issue in the canonical duality theory has been addressed, i.e., in the case that the canonical dual problem has no interior critical point in its feasible space Sa+, a quadratic perturbation method is introduced to recover the global solution through a primal-dual iterative approach, and a gradient-based method is further used to refine the solution. A series of test problems, including the benchmark polynomials and several instances of the sensor network localization problems, have been used to testify the effectiveness of the proposed algorithm. © 2013 Published by Elsevier Inc. All rights reserved.
Model modification in scheduling of batch chemical processes
- Authors: Zhou, Xiaojun , Gao, David , Yang, Chunhua
- Date: 2015
- Type: Text , Conference paper
- Relation: 3rd World Congress on Global Optimization in Engineering and Science, WCGO 2013; Anhui, China; 8th-12th July 2013 Vol. 95, p. 89-97
- Full Text: false
- Reviewed:
- Description: This paper addresses the model modification in scheduling of batch chemical processes, which is widely used in current literatures. In the modified model, the capacity, storage constraints are modified and the allocation, sequence constraints are simplified. It is shown that the modified model can lead to fewer decision variables, fewer constraints, resulting in low computational complexity. Experimental results with two classical examples are given to demonstrate the effectiveness of the proposed formulation and approach. © Springer International Publishing Switzerland 2015.
Global solutions to a class of CEC benchmark constrained optimization problems
- Authors: Zhou, Xiaojun , Gao, David , Yang, Chunhua
- Date: 2016
- Type: Text , Journal article
- Relation: Optimization Letters Vol. 10, no. 3 (2016), p. 457-472
- Full Text:
- Reviewed:
- Description: This paper aims to solve a class of CEC benchmark constrained optimization problems that have been widely studied by nature-inspired optimization algorithms. Based on canonical duality theory, these challenging problems can be reformulated as a unified canonical dual problem over a convex set, which can be solved deterministically to obtain global optimal solutions in polynomial time. Applications are illustrated by some well-known CEC benchmark problems, and comparisons with other methods have demonstrated the effectiveness of the proposed approach. © 2014, Springer-Verlag Berlin Heidelberg.
A particle swarm optimization algorithm with variable random functions and mutation
- Authors: Zhou, Xiaojun , Yang, Chunhua , Gui, Weihua , Dong, Tianxue
- Date: 2014
- Type: Text , Journal article
- Relation: Zidonghua Xuebao/Acta Automatica Sinica Vol. 40, no. 7 (2014), p. 1339 - 1347
- Full Text: false
- Reviewed:
- Description: The convergence analysis of the standard particle swarm optimization (PSO) has shown that the changing of random functions, personal best and group best has the potential to improve the performance of the PSO. In this paper, a novel strategy with variable random functions and polynomial mutation is introduced into the PSO, which is called particle swarm optimization algorithm with variable random functions and mutation (PSO-RM). Random functions are adjusted with the density of the population so as to manipulate the weight of cognition part and social part. Mutation is executed on both personal best particle and group best particle to explore new areas. Experiment results have demonstrated the effectiveness of the strategy. Copyright © 2014 Acta Automatica Sinica. All rights reserved.