An NSGA-II-Based Memetic Algorithm for an Energy-Efficient Unrelated Parallel Machine Scheduling Problem with Machine-Sequence Dependent Setup Times and Learning Effect

2021 ◽  
Author(s):  
Gulcin Bektur
Keyword(s):  
Energy Efficient ◽  
Memetic Algorithm ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Nsga Ii ◽  
Machine Sequence ◽  
Unrelated Parallel Machine Scheduling ◽  
Parallel Machine Scheduling Problem ◽  
Dependent Setup Times ◽  
Sequence Dependent Setup Times

ACO Algorithm for Scheduling Complex Unrelated Parallel Machine

2011 ◽  
Vol 268-270 ◽  
pp. 297-302
Author(s):  
Guo Bao Liu ◽  
Qiong Zhu ◽  
Jie Zhang
Keyword(s):  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Np Hard ◽  
Unrelated Parallel Machine ◽  
Unrelated Parallel Machine Scheduling ◽  
Parallel Machine Scheduling Problem ◽  
Np Hard Problem ◽  
Sequence Dependent Setup ◽  
Dependent Setup Times ◽  
Sequence Dependent Setup Times

This Paper Addresses an Unrelated Parallel Machine Scheduling Problem with Job Sequence-Dependent Setup Times. Jobs Have Precedence Constraints. the Objective Is to Minimize the Makespan. the Problem Has Applications in Industries such as TFT-LCD, Textile Manufactures. the Problem Is NP-Hard in Strong Sense. Therefore, an Ant Colony Optimization (ACO) Algorithm Is Introduced to Solve this NP-Hard Problem. the Proposed ACO Tackles the Special Structure of the Problem. its Performance Is Evaluated by Comparing its Solutions with Cplex Method. the Results Show that ACO Outperformed the Cplex Method.

A genetic algorithm with neighborhood search procedures for unrelated parallel machine scheduling problem with sequence-dependent setup times

2020 ◽  
Vol 15 (3) ◽  
pp. 809-828
Author(s):  
Levi Ribeiro de Abreu ◽  
Bruno de Athayde Prata
Keyword(s):  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Neighborhood Search ◽  
Content Type ◽  
Unrelated Parallel Machine Scheduling ◽  
Parallel Machine Scheduling Problem ◽  
Sequence Dependent Setup ◽  
Problem Instances ◽  
Dependent Setup Times ◽  
Sequence Dependent Setup Times

Purpose The purpose of this paper is to present a hybrid meta-heuristic based on genetic algorithms (GAs), simulated annealing, variable neighborhood descent and path relinking for solving the variant of the unrelated parallel machine scheduling problem considering sequence-dependent setup times. Design/methodology/approach The authors carried out computational experiments on literature problem instances proposed by Vallada and Ruiz (2011) and Arnaout et al. (2010) to test the performance of the proposed meta-heuristic. The objective function adopted was makespan minimization, and the authors used relative deviation, average and population standard deviation as performance criteria. Findings The results indicate the competitivity of the proposed approach and its superiority in comparison with several other algorithms. In small instances proposed by Vallada and Ruiz (2011) and on small and large instances proposed by Arnaout et al. (2010), the proposed approach presented the best results in most tested problem instances. Practical implications In small instances proposed by Vallada and Ruiz (2011) and on small and large instances proposed by Arnaout et al. (2010), the proposed approach presented the best results in most tested problem instances. Originality/value The proposed approach presented high-quality results, with an innovative hybridization of a GA and neighborhood search algorithms, tested in diverse instances of literature. Furthermore, the case study demonstrated that the proposed approach is recommended for solving real-world problems.

Sign in / Sign up

Export Citation Format

Share Document