Study on multi-objective flexible job-shop scheduling problem considering energy consumption
Abstract: Build a
multi-objective Flexible Job-shop Scheduling Problem(FJSP) optimization model,
in which the makespan, processing cost, energy consumption and cost-weighted
processing quality are considered, then Design a Modified Non-dominated Sorting
Genetic Algorithm (NSGA-II) based on blood variation for above scheduling
model.
Design/methodology/approach: A multi-objective optimization theory based
on Pareto optimal method is used in carrying out the optimization model. NSGA-II
is used to solve the model.
Findings: By analyzing the research status and insufficiency of
multi-objective FJSP, Find that the difference in scheduling will also have an
effect on energy consumption in machining process and environmental emissions.
Therefore, job-shop scheduling requires not only guaranteeing the processing
quality, time and cost, but also optimizing operation plan of machines and
minimizing energy consumption.
Originality/value: A multi-objective FJSP optimization model is put forward,
in which the makespan, processing cost, energy consumption and cost-weighted
processing quality are considered. According to above model,
Blood-Variation-based NSGA-II (BVNSGA-II) is designed. In which, the chromosome
mutation rate is determined after calculating the blood relationship between
two cross chromosomes, crossover and mutation strategy of NSGA-II is optimized
and the prematurity of population is overcome. Finally, the performance of the
proposed model and algorithm is evaluated through a case study, and the results
proved the efficiency and feasibility of the proposed model and algorithm.
Keywords: Multi-objective
Scheduling; Flexible Job-shop Scheduling; NSGA-?; Energy Consumption; Blood
Variation
Author: Zengqiang Jiang, Le
Zuo, Mingcheng E
Journal Code: jptindustrigg140072
