In this paper, we propose a new population-based framework for combining local search with global explorations to solve single-objective unconstraint numerical optimization problems. The idea is to use knowledge about local optima found during the search to a) locate promising regions in the search space and b) identify the suitable step size to move from one optimum to others in each region. T...

This study presents a new method for knowledge transfer in Multi-Population Cultural Algorithms (MPCA) through agent migration. This agent-based algorithm involves having individual agents using one of multiple pre-defined knowledge algorithms to determine behavior, and using the success of it and other agents to decide on which knowledge algorithms to use next. Two or more subpopulations with ...

A cultural algorithm is proposed in this paper. The main novel feature of this approach is the use of differential evolution as a population space. Differential evolution has been found to be very effective when dealing with real valued optimization problems. The knowledge sources contained in the belief space of the cultural algorithm are specifically designed according to the differential evo...

The Land Bridge – Cultural Algorithms Program Simulation (L-CAPS) system is a functional interface for learning group behavior using Cultural Algorithms (CA). It enables the Cultural Algorithms process to implicitly communicate with, modify, and evaluate autonomous game agents restricted to an external virtual world. The L-CAPS system extends the work of Kinnaird-Heether (Reynolds & Kinnaird-He...

Cultural Algorithms (CAs) are one of the metaheuristics which can adapt in order to work in multi-objectives optimization environments. On the other hand, Bi-Objective Uncapacitated Facility Location Problem (BOUFLP) and particularly Uncapacitated Facility Location Problem (UFLP) are a well know problems in literature. However, a few articles have worked in the sense of applied evolutionary mul...