Particle swarm optimization (PSO) is originally developed as an unconstrained optimization technique, therefore lacks an explicit mechanism for handling constraints. When solving constrained optimization problems (COP...
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Particle swarm optimization (PSO) is originally developed as an unconstrained optimization technique, therefore lacks an explicit mechanism for handling constraints. When solving constrained optimization problems (COPs) with PSO, the existing research mainly focuses on how to handle constraints, and the impact of constraints on the inherent search mechanism of PSO has been scarcely explored. Motivated by this fact, in this paper we mainly investigate how to utilize the impact of constraints (or the knowledge about the feasible region) to improve the optimization ability of the particles. Based on these investigations, we present a modified PSO, called self-adaptive velocity particle swarm optimization (SAVPSO), for solving COPs. To handle constraints, in SAVPSO we adopt our recently proposed dynamic-objective constraint-handling method (DOCHM), which is essentially a constituent part of the inherent search mechanism of the integrated SAVPSO, i.e., DOCHM + SAVPSO. The performance of the integrated SAVPSO is tested on a well-known benchmark suite and the experimental results show that appropriately utilizing the knowledge about the feasible region can substantially improve the performance of the underlying algorithm in solving COPs.
Considering a generic nonlinear programming problem (NLPP), this paper provides a family of linear infinite problems (LIPs) or linear semi-infinite problems (LSIPs), and establishes the connection between optimality i...
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Considering a generic nonlinear programming problem (NLPP), this paper provides a family of linear infinite problems (LIPs) or linear semi-infinite problems (LSIPs), and establishes the connection between optimality in the respective NLPP and that in the provided LIPs (LSIPs). (C) 2007 Elsevier B.V. All rights reserved.
We give several linear time algorithms for the continuous quadratic knapsack problem. In addition, we report cycling and wrong-convergence examples in a number of existing algorithms, and give encouraging computationa...
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We give several linear time algorithms for the continuous quadratic knapsack problem. In addition, we report cycling and wrong-convergence examples in a number of existing algorithms, and give encouraging computational results for large-scale problems.
Recent research has shown that the load flow equations describing the steady-state conditions in a meshed network can be placed in extended conic quadratic (ECQ) format. This paper presents a study of the implementati...
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Recent research has shown that the load flow equations describing the steady-state conditions in a meshed network can be placed in extended conic quadratic (ECQ) format. This paper presents a study of the implementation of the new load flow equations format in an optimal power flow (OPF) program which accounts for control devices such as tap-changing transformers, phase-shifting transformers, and unified power flow controllers. The proposed OPF representation retains the advantages of the ECQ format: 1) it can be easily integrated within optimization routines that require the evaluation of second-order derivatives, 2) it can be efficiently solved for using primal-dual interior-point methods, and 3) it can make use of linear programming scaling techniques for improving numerical conditioning. The ECQ-OPF program is employed to solve the economic dispatch and active power loss minimization problems. Numerical testing is used to validate the proposed approach by comparing against solution methods and results of standard test systems.
In a competitive electricity market two kinds of generating companies coexist;according to their market power it possible to classify them in price-taking generating companies and leader generating companies. The opti...
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In a competitive electricity market two kinds of generating companies coexist;according to their market power it possible to classify them in price-taking generating companies and leader generating companies. The optimal bidding of price-taking companies depends on the market clearing prices. On the other hand, the optimal bidding of leader companies depends on their corresponding residual demand curves, which capture how the market clearing price changes with the variation on the levels production of a particular generating company. The idea of this article is to assess the potential market power of a leader company when it decides to compete in quantities according to the Cournot model. A non-linear optimization problem has been used to model the lemel the dleader generating company. Finally, a realistic case study is presented and discussed.
A branch and bound (B& B) algorithm using the DC model, to solve the power system transmission expansion planning by incorporating the electrical losses in network modelling problem is presented. This is a mixed i...
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A branch and bound (B& B) algorithm using the DC model, to solve the power system transmission expansion planning by incorporating the electrical losses in network modelling problem is presented. This is a mixed integer nonlinear programming (MINLP) problem, and in this approach, the so-called fathoming tests in the B&B algorithm were redefined and a nonlinear programming (NLP) problem is solved in each node of the B& B tree, using an interior-point method. Pseudocosts were used to manage the development of the B&B tree and to decrease its size and the processing time. There is no guarantee of convergence towards global optimisation for the MINLP problem. However, preliminary tests show that the algorithm easily converges towards the best-known solutions or to the optimal solutions for all the tested systems neglecting the electrical losses. When the electrical losses are taken into account, the solution obtained using the Garver system is better than the best one known in the literature.
An equivalent current injection (ECI)-based hybrid current-power optimal power flow (OPF) model is proposed in this paper, and the predictor-corrector interior point algorithm (PCIPA) is tailored to fit the OPF for so...
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An equivalent current injection (ECI)-based hybrid current-power optimal power flow (OPF) model is proposed in this paper, and the predictor-corrector interior point algorithm (PCIPA) is tailored to fit the OPF for solving nonlinear programming (NLP) problems. The proposed method can further decompose into two subproblems. The computational results of IEEE 9 to 300 buses have shown that the proposed algorithms can enhance the performance in terms of the number of iterations, memory storages, and CPU times.
We suggest a new heuristic for solving unconstrained continuous optimization problems. It is based on a generalized version of the variable neighborhood search metaheuristic. Different neighborhoods and distributions,...
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We suggest a new heuristic for solving unconstrained continuous optimization problems. It is based on a generalized version of the variable neighborhood search metaheuristic. Different neighborhoods and distributions, induced from different metrics are ranked and used to get random points in the shaking step. We also propose VNS for solving constrained optimization problems. The constraints are handled using exterior point penalty functions within an algorithm that combines sequential and exact penalty transformations. The extensive computer analysis that includes the comparison with genetic algorithm and some other approaches on standard test functions are given. With our approach we obtain encouraging results. (C) 2007 Elsevier B.V. All rights reserved.
This paper concerns the development of a kinematic formulation for the finite element limit and shakedown analysis of shells. The technique is based upon an upper bound approach using the re-parameterized exact Ilyush...
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This paper concerns the development of a kinematic formulation for the finite element limit and shakedown analysis of shells. The technique is based upon an upper bound approach using the re-parameterized exact Ilyushin yield surface and a nonlinear optimization procedure. The solution of the problem is obtained by discretizing the shell into finite elements, Numerical examples are presented to show the validity of the present method. (C) 2008 Elsevier Ltd. All rights reserved.
A new SVM model used to calculate the optimal value of cost parameter C for particular problems of linearity non-separability of data is presented in this paper. The new SVM model is formulated in the form of one of M...
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A new SVM model used to calculate the optimal value of cost parameter C for particular problems of linearity non-separability of data is presented in this paper. The new SVM model is formulated in the form of one of MPEC problems with an integer objective function. A lower bound, positive number, C-0 is required to provide for avoiding choosing a candidate set of C. Numerical experiments show that this model for choice of C is suitable for solving SVM problems. (C) 2007 Elsevier Ltd. All rights reserved.
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