A Genetic Algorithm for the Parallel Machine Scheduling Problem with Consumable Resources

2013 ◽  
Vol 4 (2) ◽  
pp. 17-30 ◽  
Author(s):  
Fayçal Belkaid ◽  
Zaki Sari ◽  
Mehdi Souier
Keyword(s):  
Genetic Algorithm ◽  
Parallel Machines ◽  
Optimization Problems ◽  
Parallel Machine Scheduling ◽  
Scheduling Problem ◽  
Combinatorial Optimization Problems ◽  
Great Performance ◽  
Parallel Machine Scheduling Problem ◽  
Exact Resolution ◽  
Makespan Criterion

In this paper, the authors’ interest is focused on the scheduling problem on identical parallel machines with consumable resources in order to minimize the makespan criterion. Each job consumes several components which arrive at different times. The arrival of each component is represented by a curve-shaped staircase. This problem is NP-hard, further, there are not universal methods making it possible to solve all the cases effectively, especially for medium or large instances. A genetic algorithm is proposed to solve this problem due to proven great performance in solving combinatorial optimization problems. To check its effectiveness this algorithm is compared with an exact resolution method which enumerates all possible solutions for small instances and with a heuristic for large instances. Various randomly generated instances, which can represent realistic situations, are tested. The computation results show that this algorithm outperforms heuristic procedure and is tailored for larger scale problems.

scholarly journals IDENTICAL PARALLEL MACHINES SCHEDULING USING GENETIC ALGORITHM

2018 ◽  
Vol 18 (2) ◽  
pp. 321-330
Author(s):  
Aseel J Haleel
Keyword(s):  
Genetic Algorithm ◽  
Processing Time ◽  
Parallel Machines ◽  
Machine Scheduling ◽  
Setup Time ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Scheduling Problem ◽  
Identical Parallel Machine ◽  
Parallel Machine Scheduling Problem

Minimizing the scheduling production time consider one of the most important factors forcompanies which their objectives is achieve the maximum profits. This paper studies theidentical parallel machine scheduling problem which involves the assignment numbers ofjob (N) to set of identical parallel machine (M) in order to minimize the makespan(maximum completion time of all job). There are numerous troubles in solving the largesize of “parallel machine scheduling” problem with an excessive jobs and machines, sothe genetic algorithm was proposed in this paper which is consider an efficient algorithmthat fits larger size of identical “parallel machine scheduling” for minimizing themakespan. Most studies in the scheduling field suppose setup time is insignificant orincluded in the processing time, in this paper both the sequence independent setup timesand processing time were considered. The solutions of algorithms are coding in(MATLAB). A numerical example of (11) jobs are schedule on (3) machines todemonstrative the effectiveness of algorithm solution. The result show the algorithm caneffectively solve large size of scheduling problem and given the best schedule withminimum makespan.

The Simulation Optimization for Job-Shop Scheduling Based on Plant Simulation Using Genetic Algorithm

2012 ◽  
Vol 217-219 ◽  
pp. 1444-1448
Author(s):  
Xiang Ke Tian ◽  
Jian Wang
Keyword(s):  
Genetic Algorithm ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Optimization Problems ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Combinatorial Optimization Problems ◽  
Plant Simulation

The job-shop scheduling problem (JSP), which is one of the best-known machine scheduling problems, is among the hardest combinatorial optimization problems. In this paper, the key technology of building simulation model in Plant Simulation is researched and also the build-in genetic algorithm of optimizing module is used to optimize job-shop scheduling, which can assure the scientific decision. At last, an example is used to illustrate the optimization process of the Job-Shop scheduling problem with Plant Simulation genetic algorithm modules.

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