Genetic algorithm to solve a multi-objective scheduling problem
Citation
Mouzon, Gilles & Yildirim, Mehmet B. (2007). Genetic algorithm to solve a multi-objective scheduling problem. In Proceedings : 3rd Annual Symposium : Graduate Research and Scholarly Projects. Wichita, KS : Wichita State University, p.45-46
Abstract
Energy is expensive and a potential way to
reduce energy consumption may be through using intelligent
scheduling techniques. In this paper, we propose a genetic
algorithm to solve a single machine scheduling problem
where the objectives are minimizing total completion time
and energy consumption of manufacturing equipment when
all of the processing time and release dates of the job are
known. This problem has several applications including
scheduling in manufacturing industry, energy minimization
in computers, cell phones, sensors, etc. Different fitness
functions and parameters depending on the problem's
characteristics were tested using a design of experiment
approach. The proposed methodology generates several
pareto optimal solutions. A decision maker can select one of
these solutions using Analytical Hierarchical Process.
Description
Paper presented to the 3rd Annual Symposium on Graduate Research and Scholarly Projects (GRASP) held at the Hughes Metropolitan Complex, Wichita State University, April 27, 2007.
Research completed at the Department of Industrial and Manufacturing Engineering, College of Engineering