To address the problem of sparrow search algorithm (SSA) has poor global ability, weak local development and easily falls into optimal solution, a multi-strategy improved evolutionary (MSSA) is proposed. The introduction tent chaotic map improves diversity initialization population, accelerates convergence, convergence accuracy. Endow finders with random ability to coordinate balance between de...

The development of a sound theory that predicts and veriies existing evolutionary algorithms is one of the most important research issues in the eld today. In mathematical proofs, the assumption of spherical symmetry is probably one of the most widely-used simpliications. This paper discusses to which extend spherical symmetry is appropriate for certain evolutionary algorithms. It turns out tha...

Timetabling problems are often hard and time­consuming to solve. Most of the methods of solving them concern only one problem instance or class. This paper describes a universal method for solving large, highly constrained timetabling problems from different domains. The solution is based on evolutionary algorithm’s framework and employs tabu search to speed up the solution finding...

The problem of triangulation (decomposition) of Bayesian networks is considered. Triangularity of a Bayesian network is required in a general evidence propagation scheme on this network. Finding an optimal triangulation is NP-hard. A local search heuristic based on the idea of evolutionary algorithms is presented. The results obtained using existing and proposed approaches are compared on a bas...

The representations currently used by local search and some evolutionary algorithms have the disadvantage that these algorithms are partially blind to “ridges” in the search space. Both heuristics search and gradient search algorithms can exhibit extremely slow convergence on functions that display ridge structures. A class of rotated representations are proposed and explored; these rotated rep...

In the field of Evolutionary Computation, a common myth that “An Evolutionary Algorithm (EA) will outperform a local search algorithm, given enough runtime and a large-enough population” exists. We believe that this is not necessarily true and challenge the statement with several simple considerations. We then investigate the population size parameter of EAs, as this is the element in the above...

A new search model for evolutionary algorithms is proposed. This model is based on the simultaneously run of two different search operators. It is a good way to attend equilibrium between the exploration and the exploitation of the search space. By means of a basic evolutionary algorithm, it is proved that the proposed method improves the solution of the problem, and the resources needed to att...

Evolutionary testing is a search based approach to the automated generation of systematic test data, in which the search is guided by the test data adequacy criterion. Two problems for evolutionary testing are the large size of the search space and structural impediments in the implementation of the program which inhibit the formulation of a suitable fitness function to guide the search. In thi...