Solving Multi Objectives Machine Scheduling Problem using Evolving Algorithms

Abstract—In the current research, we find approximate solutions to a multi-objective machine scheduling problem (MOMSP) by minimizing the multi-objective function (∑_(j=1)^n▒〖(E_j+T_j+C_j+U_j+V_j 〗)). The approximate solutions are founded by using Particle Swarm Optimization (PSO) and Bat Algorithm on some laboratory problems and compare them with some exact methods (branch and bound and complete enumeration). The results prove the efficiency of PSO and BAT in solving MOMSP. Keywords—Machine Scheduling Problems, Multi-Objectives, Local Search Method, Evolving Algorithms, Bat Algorithm, Particle Swarm Optimization.