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Comparison of Three Metaheuristic Algorithms for Optimization of Cyber Physical Systems

Although the paradigm of Cyber-Physical Systems (CPS) enable manufacturers to respond to challenges in the dynamic business environment, it relies on an effective resource allocation mechanism to optimize production processes. In the past years, the production processes optimization problem in CPS has been formulated and solved by applying discrete version of Particle Swarm Optimization (PSO) called DPSO and binary Differential Evolution (DE) called BDE. The DPSO algorithm is based on a transformation function that maps real values into discrete values. The BDE algorithm uses mutation mechanism that create mutant vectors based on logical operations on individuals in the population without relying on a transformation function. In this paper, another discrete version of Differential Evolution (DE) called DDE is proposed and applied to optimize production processes in CPS. We conduct experiments to compare these algorithms based on numerical results.