Search

Abstract: The 0-1 knapsack problem is an open issue in discrete optimization problems, which plays an important role in real applications. In this paper, a new bio-inspired model is proposed to solve this problem. The proposed method has three main steps. First, the 0-1 knapsack problem is converted into a directed graph by the network converting algorithm. Then, for the purpose of using the amoeboid organism model, the longest path problem is transformed into the shortest path problem. Finally, the shortest path problem can be well handled by the amoeboid organism algorithm. Numerical examples are given to illustrate the efficiency of the proposed model. [Copyright &y& Elsevier]

Abstract: Recently, a new class of stochastic optimization algorithm called SOMA (self-organizing migrating algorithm) was proposed in the literature. SOMA works on a population of potential solutions called specimen and it is based on the self-organizing behavior of groups of individuals in a “social environment”. This paper proposes a SOMA approach combined with a cultural algorithm (CSOMA) technique based on normative knowledge as an alternative method to solving the economic load dispatch problem of thermal generators with the valve-point effect. The classical SOMA and CSOMA approaches are validated for two test systems consisting of 13 and 40 thermal generators whose non-smooth fuel cost function takes into account the valve-point loading effects. Numerical results indicate that performance of the CSOMA present best results when compared with results of others optimization methods found in the literature in solving load dispatch problems with the valve-point effect. [ABSTRACT FROM AUTHOR]