This paper proposes a novel global harmony search algorithm (NGHS) to solve 0–1 knapsack problems. Theproposed algorithm includes two important operations: positionupdating andgeneticmutationwith a small probability. The former enables the worst harmony of harmony memory to move to the global best harmony rapidly in each iteration, and the latter can effectively prevent theNGHS from trapping in...

Abstract: In this paper, a new fuzzy harmony search algorithm (FHS) for solving optimization problems is presented. FHS is based on a recent method using fuzzy logic for dynamic adaptation of the harmony memory accepting (HMR) and pitch adjustment (PArate) parameters that improve the convergence rate of traditional harmony search algorithm (HS). The objective of the method is to dynamically adj...

ALI SHANON ALSAADI, TAT-CHEE WAN AND ALHAMZA MUNTHER Computer Engineering and Computer Science Department University of Louisville Louisville, KY 40292 USA School of Computer Sciences Universiti Sains Malaysia Penang, 11800 Malaysia School of Computer and Communication Engineering Universiti Malaysia Perlis Perlis, 02600 Malaysia E-mail: [email protected]; [email protected]; g1340811014@...

Wastewater pumping consumes 10% to 20% of electricity in wastewater treatment plants. To reduce the energy consumption, a data-driven approach is applied to model and optimize the wastewater pumping process. Datamining algorithm and multilayer perceptron neural network are used to build the pumping energy model. The optimization model is solved by an improved harmony search algorithm. Optimal p...

Harmony Search metaheuristic is successfully used in several applications of science and engineering. However, its effectiveness in solving multiobjective optimization problems using the concepts of Pareto optimality, remains unproved. This paper presents two proposals of the Harmony Search metaheuristic for multiobjective optimization, using the ZDT functions as a test bed. Performance metrics...

The harmony search (HS) is a music-inspired evolutionary algorithm, mimicking the improvisation process of music players (Geem et al., 2001). The HS is simple in concept, few in parameters, and easy in implementation, with theoretical background of stochastic derivative (Geem, 2007a). The algorithm was originally developed for discrete optimization and later expanded for continuous optimization...

the cuckoo search algorithm is a recently developedmeta-heuristic optimization algorithm, which is suitable forsolving optimization problems. to enhance the accuracy andconvergence rate of this algorithm, an improved cuckoo searchalgorithm is proposed in this paper. normally, the parametersof the cuckoo search are kept constant. this may lead todecreasing the efficiency of the algorithm. to cop...