Enerji tasarrufu için iş istasyonu planlama ve programlama gereksinimleri

Reducing energy consumption is a major challenge in many industries and it is not easy and has a direct and positive impact on preserving our lives first and the environment second by reducing emissions, as energy in the industrial section has increased in the past fifty years, as energy consumption is estimated to be output from industry. Minimizing energy consumption is an important aspect of planning and scheduling manufacturing processes. This leads to a multiple objective environment for the scheduling problems. In this thesis we considered a multi-objective scheduling problem in which the objectives are minimizing the makespan and energy consumption. We offered a new multi-objective Genetic Algorithm in which there are separate populations for different objectives and there is a mixing mechanism in the parent selection and crossover phases to improve both objectives simultaneously. We then presented an algorithmic implementation to tackle the problem. Simulation results for different parameter settings is given. We believe that this kind of genetic algorithm design can be beneficial in scheduling problems which aims to minimize energy consumption beside the other time-related objective like makespan.