Seminer: Mert Paldrak, “An Ensemble of Differential Evolution Algorithms for Real-Parameter Optimization and Its Application to Multidimensional Knapsack Problem”

AN ENSEMBLE OF DIFFERENTIAL EVOLUTION ALGORITHMS FOR REAL-PARAMETER OPTIMIZATION AND ITS APPLICATION TO MULTIDIMENSIONAL KNAPSACK PROBLEM

An ensemble of differential evolution algorithms based on a variable neighborhood search algorithm (EDE-VNS) is proposed so as to solve the constrained real parameter-optimization problems. The performance of DE algorithms heavily depends on the mutation strategies, crossover operators and control parameters employed. The proposed EDE-VNS algorithm employs multiple mutation operators and control parameters in its VNS loops to enhance the solution quality. In addition, we utilize opposition-based learning (OBL) to take advantages of opposite solutions to find a candidate solution which might be close to the global optimum. In addition, we also present an idea of injecting some good dimensional values from promising areas in the population to the trial individual through the injection procedure. The computational results show that the EDE-VNS algorithm is very competitive to some of the best performing algorithms from the literature.

SHORT BIO

Mert Paldrak was born in İzmir/Konak in 1991. He has been working as a research assistant at the Department of Industrial Engineering at Yaşar University in İzmir since October 2013. He has received his BSc degree in Industrial Engineering with the 2nd degree from Yaşar University Engineering Faculty in 2013 and then he continued his MSc degree in Industrial Engineering in Yaşar University Engineering Faculty. During his master degree period, he has taken such various courses as System Simulation, Optimization Models and Algorithms, Heuristic Optimization, Scheduling Theory, Probabilistic Analysis and Applied Stochastic Processes, Dynamic Programming, Mathematics of Operational Research and Supply Chain and Management.