Genetic Algorithm Based Optimization for Energy-aware Hybrid Flow Shop Scheduling
نویسندگان
چکیده
Based on MATLAB/SimEvents simulation platform and genetic algorithm, the simulation and optimization of energy consumption in hybrid flow shop is studied. Considering workshop layout and workpiece path, machining process simulation in hybrid flow shop is realized. With the processing time, processing power and stand-by power introduced into simulation model, the energy consumption simulation in hybrid flow shop is achieved. Genetic algorithm based weighted optimization method is employed to optimize the energy consumption simulation model, which takes the minimum makespan and minimum energy consumption as optimization objectives. Finally, a case study is performed to verify the effectiveness of the simulation model and optimization method, and analysis on optimization results is carried out.
منابع مشابه
Scheduling of a flexible flow shop with multiprocessor task by a hybrid approach based on genetic and imperialist competitive algorithms
This paper presents a new mathematical model for a hybrid flow shop scheduling problem with multiprocessor tasks in which sequence dependent set up times and preemption are considered. The objective is to minimize the weighted sum of makespan and maximum tardiness. Three meta-heuristic methods based on genetic algorithm (GA), imperialist competitive algorithm (ICA) and a hybrid approach of GA a...
متن کاملImproved teaching–learning-based and JAYA optimization algorithms for solving flexible flow shop scheduling problems
Flexible flow shop (or a hybrid flow shop) scheduling problem is an extension of classical flow shop scheduling problem. In a simple flow shop configuration, a job having ‘g’ operations is performed on ‘g’ operation centres (stages) with each stage having only one machine. If any stage contains more than one machine for providing alternate processing facility, then the problem...
متن کاملA novel mathematical model for a hybrid flow shop scheduling problem under buffer and resource limitations-A case study
Scheduling problems play a big role in manufacturing and planning the production for increasing the production efficiency and assigning the resources to operations. Furthermore, in many manufacturing systems there is a physical space between stages that called intermediate buffers. In this study, a model is proposed for minimizing the makespan of a hybrid flow shop scheduling problem with inter...
متن کاملThree Hybrid Metaheuristic Algorithms for Stochastic Flexible Flow Shop Scheduling Problem with Preventive Maintenance and Budget Constraint
Stochastic flexible flow shop scheduling problem (SFFSSP) is one the main focus of researchers due to the complexity arises from inherent uncertainties and also the difficulty of solving such NP-hard problems. Conventionally, in such problems each machine’s job process time may encounter uncertainty due to their relevant random behaviour. In order to examine such problems more realistically, fi...
متن کاملA novel hybrid genetic algorithm to solve the make-to-order sequence-dependent flow-shop scheduling problem
Flow-shop scheduling problem (FSP) deals with the scheduling of a set of n jobs that visit a set of m machines in the same order. As the FSP is NP-hard, there is no efficient algorithm to reach the optimal solution of the problem. To minimize the holding, delay and setup costs of large permutation flow-shop scheduling problems with sequence-dependent setup times on each machine, this pap...
متن کامل