Constrained optimization problems are with great difficulties to be solved for the complex influences of their constraints. However, many crossover operators in the constrained evolutionary ...algorithms have a disadvantage on bias search of the boundary. A novel uniform design based crossover operator coupled with a new space searching strategy aiming to overcome this disadvantage are proposed in this paper. Based on this, a hybrid evolutionary algorithm with domination clustering is constructed to solve constrained multiobjective optimization problems. Experiments on 13 benchmarks are made, and the results are conpared with existing algorithms to demonstrate the effectiveness and positiveness of the proposed algorithm.
A new immune optimization algorithm for constrained multiobjective optimization problems is designed based on danger theory exhibited in biological immune system. The general situation and running ...mechanism are presented in this paper. The algorithm identifies "dangerous" as the core idea and introduces antigen presenting cell and different danger signals. Experimental results of constrained multiobjective optimization show that the new algorithm has higher efficiency than traditional immune algorithms.
The use of evolutionary algorithms (EAs) to solve problems with multiple objectives (known as multiobjective optimization problems (MOPs)) has attracted much attention recently. Population based ...approaches, such as EAs, offer a means to find a group of Pareto-optimal solutions in a single run. However, most studies are undertaken on unconstrained MOPs. Recently, we developed the co-evolutionary algorithms for unconstrained MOPs. The objective of this paper is to introduce a modification to co-evolutionary algorithms for handling constraints. The solutions, provided by the proposed algorithm for one test problem, are promising when compared with an existing well-known algorithm.
To enhance the robustness and stability of the antenna design, a novel methodology is presented for modelling the antenna design problem as the constrained optimisation problem (COP). Then a ...framework is introduced for solving the COP. The framework converts a COP into an equivalent dynamic constrained multi-objective optimisation problem (DCMOP). A dynamic constrained multi-objective evolutionary algorithm is applied to address the transformed DCMOP, which means the COP as well as the antenna design problem can be solved. Then it is applied to design three classes of antennas: a wire antenna, a patch antenna and an antenna array. Obtained results of these three kinds of antenna suggest that the proposed methods can well satisfy the antenna design requirements.
This study proposes a new model for long-term planning of large-scale wind farms (WFs) considering voltage stability constraints. The proposed model is a multi-objective optimisation problem which ...aims to maximise the profit of WF investor from wind energy procurement and to minimise the overall power generation cost. By performing modal analysis on the reduced power flow Jacobian matrix, proper locations for installation of WFs are determined. Moreover, the impact of voltage stability constraints on the capacity of WFs is investigated. In comparison with other studies, the main contributions of this study are: (i) to propose a new methodology for determination of the best locations for WFs, (ii) to study the impact of voltage stability as an important security constraint in long-term planning of wind energy. The proposed voltage stability constrained multi-objective wind power planning (VSC-MOWPP) model is solved via ɛ-constraint method in General Algebraic Modelling System optimisation package environment. The compromise solution of Pareto optimal set is selected using fuzzy satisfying approach. The proposed VSC-MOWPP model is examined on the IEEE 39-bus standard test system. The numerical investigations substantiate the suitability of the proposed model for multi-year planning of WFs at the presence of long-term voltage stability constraints.
This study presents a methodology for distribution system (DS) reconfiguration in the presence of distributed generations with objectives of minimising real power loss, switching operations as well ...as maximising the voltage stability margin while maintaining the constraints of bus voltage, branch current carrying capacity and radiality of DS. Furthermore, small signal stability of the system has also been considered in the formulated reconfiguration problem. To obtain the pareto‐optimal solutions of this constrained multi‐objective optimisation problem, knee point‐driven evolutionary algorithm, is applied. In contrast to the non‐dominated sorting genetic algorithm‐II (NSGA‐II)‐based approach, preference is given to the knee points among non‐dominated solutions in selection and tournament mating. Therefore, it maintains better balance between the convergence of the method and the diversity in the population. The method has been tested on IEEE 33‐bus, 69‐bus and 119‐bus radial DSs to demonstrate its feasibility and effectiveness. The obtained results have also been compared with those obtained by the multi‐objective NSGA‐II‐based method.
The present paper considers the optimisation of process parameters in friction stir welding (FSW). More specifically, the choices of rotational speed and traverse welding speed have been investigated ...using genetic algorithms. The welding process is simulated in a transient, two-dimensional sequentially coupled thermomechanical model in ANSYS. This model is then used in an optimisation case where the two objectives are the minimisation of the peak residual stresses and the maximisation of the welding speed. The results indicate that the objectives for the considered case are conflicting, and this is presented as a Pareto optimal front. Moreover, a higher welding speed for a fixed rotational speed results, in general, in slightly higher stress levels in the tension zone, whereas a higher rotational speed for a fixed welding speed yields somewhat lower peak residual stress, however, a wider tension zone, leading to a substantially higher residual tensile force.
