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A "basin of attraction" is a set of solutions arriving at the same local optimal solution by Best-improvement Local Search. By utilizing the concept of basin of attraction in the solution space of combinatorial optimization problem, the solution space is interpreted as a higher structure, which is a set of basin of attraction, and a lower structure, which is a set of solutions, in this paper...
Recently, the development of high-performance metaheuristics has become an important subject. In this study, an adaptive Cuckoo Search based on ranking of search point is proposed. This study aims to improve the performance of Cuckoo Search by adjusting the parameter β to allow search points with good evaluation value to search nearby and those with poor evaluation value to search far away. Finally,...
We analyzed the search characteristics of Firefly Algorithm (FA), which has a fundamental nature of a Superior Solution Set Search Problem, previously defined in our previous study for single-objective optimization problems. In this study, we proposed a new FA method based on the former problem. This method, which employs cluster information by K-means clustering, is tested for performance by fundamental...
In this paper, we propose a new search strategy based on functional specialization for multi-objective optimization and a new multi-objective optimization method. The proposed strategy is based on two ideas. The first idea is the state evaluation and classification of search points to realize an advanced search structure. The second idea is to use operations with different features to achieve an efficient...
This paper proposes a new formulation for single-objective optimization problems and a Firefly Algorithm (FA)-based optimization method for problem formulation. The formulated problem requires a set of solutions with approximately the same evaluation values and appropriate differences in relation to decision variables. In addition, the FA-based optimization method was developed based on an analysis...
In this paper, we focus on Cuckoo Search (CS) that is one of metaheuristics, and propose an adaptive CS to improve its search performance and usability. First, we analyze basically and qualitatively the effects of CS's parameter on its search dynamics. Second, from the analysis results, we define an indicator that evaluates the search state of CS based on the effective metaheuristics strategy. Moreover,...
A big valley structure is known to exist as the landscape of solution-objective function value spaces in a multitude of combinatorial optimization problems. However, this paper proposes new meta-heuristics for combinatorial optimization problems based on the degree of establishment of the big valley structure. The performance of the proposed combinatorial optimization method is verified through simulations...
Recently, the authors proposed a new metaheuristics method for continuous optimization problems based on analogy of spiral phenomena in nature which is called Spiral Optimization. The focused spiral phenomena are spirals which are approximated to logarithmic spirals. The Spiral Optimization utilizes a feature of the logarithmic spirals for global optimization. The Spiral Optimization has two tuning...
In this paper, a new optimization method based on a combination of Differential Evolution (DE) and Evolution Strategy (ES), which belong to both Meta-Heuristics and Evolutionary Computation, are developed as a fast approximation optimization method. A weak point of DE is weak local search ability and considerable computation time for obtaining a good approximate solution. The proposed method aims...
Metaheuristics is a framework of practical methods for global optimization problems. We recently proposed a new metaheuristics method inspired from spiral phenomena in nature which is called spiral optimization. However, the spiral optimization was restricted to 2-dimensional continuous optimization problems. In this paper, we develop a spiral optimization method for n-dimensional continuous optimization...
Recently we proposed a new multipoint search method in metahuristics for only 2-dimensional continuous optimization problems based on analogy of spiral phenomena in nature which is called 2-dimensional spiral optimization. The focused spiral phenomena which appear frequently in nature are approximated to logarithmic spirals. The 2-dimensional spiral optimization utilizes a feature of logarithmic spirals...
This paper proposes a new method for solving combinatorial optimization problems on the basis of Proximate Optimality Principle (POP). The proposed method has higher optimality and lower computational complexity than conventional methods. The proposed method is applied to several typical combinatorial optimization problems in order to verify the performance of the proposed method.
Differential Evolution (DE) is based on both an evolutionary strategy and a parallel direct search method employing a population. DE is an effective optimization method available for solving global optimization problem over continuous space. DE has a few control parameters that have to be set by users. This paper describes a new DE using Down-hill Simplex Method. Then we consider average distance...
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