Many local search methods apply also to problems in continuous spaces. Linear programming and convex optimization problems obey certain restrictions on the shape of the state space and the nature of the objective function, and admit polynomial-time algorithms that are oftenly extremely efficient in pra...
Continuous optimizationNumeric functionSearch strategyThe artificial bee colony, ABC for short, algorithm is population-based iterative optimization algorithm proposed for solving the optimization problems with continuously-structured solution space. Although ABC has been equipped with powerful global search ...
We present an algorithm that is inspired by theoretical and empirical results in social learning and swarm intelligence research. The algorithm is based on a framework that we call incremental social learning . In practical terms, the algorithm is a hybrid between a local search procedure and a ...
We further propose a filtering method that restricts the search space in the neighborhoods to avoid many solutions having no prospect of improvement. We then develop an iterated local search algorithm that incorporates all the above ingredients. Finally we report computational results of our iterated ...
In addition, a careful inspection of current MWVC heuristic algorithms shows that most heuristic functions are static during the local search. This would cause the algorithm to be trapped in local optima, thereby leading to bad solutions. To address the above-mentioned issues, the present paper ...
Local search algorithm Cluster analysis and community detection share many conceptual similarities, but often have a contrasting focus. Cluster analysis puts emphasis on the center of a cluster15,16, while community boundaries often play a more predominant role in community detection37. Community centers...
Differential Evolution (DE) does not become stuck in a local minimum but the tuning parameters need improvement. Genetic Algorithm (GA) has good coverage of initial solutions in the search space, but the convergence is slow [74]. Another advantage of GA over traditional optimization is its ...
Despite its simplicity, the proposed algorithm seems to have very good performance on various test problems. Numerical results are shown in order to justify the use of a double local search instead of a single search. In addition, the SFLSDE has been compared with a standard DE and three ...
The main drawback is that the TS method easily stuck in the local optimum solution. A nodal ant colony optimization (NACO) algorithm was proposed to ameliorate the solution quality of the PBUCP [27]. The search space of the NACO consists of binary nodes, which represents the ON/OFF status...
We also compared the spatial similarity between predictors (the similarity of the 400 × 1 vectors of variance explained at each region) and used an embedding algorithm to assign predictors locations in two-dimensional space based on that similarity (Fig. 2b). Fig. 2: Explaining regional ...