Using Branch and Bound and Local Search Methods to Solve Multi-objective Machine Scheduling Problem

2019 ◽  
Author(s):  
Doha Adel Abbass
Keyword(s):  
Local Search ◽  
Branch And Bound ◽  
Machine Scheduling ◽  
Scheduling Problem ◽  
Search Methods ◽  
Multi Objective ◽  
Local Search Methods

scholarly journals Minimizing the Total Completion Time and Total Earliness Time Functions for a Machine Scheduling Problem Using Local Search Methods

2020 ◽  
pp. 126-133
Author(s):  
Faez Hassan Ali ◽  
Aseel Aboud Jawad
Keyword(s):  
Particle Swarm Optimization ◽  
Local Search ◽  
Completion Time ◽  
Heuristic Methods ◽  
Scheduling Problem ◽  
Branch And Bound Method ◽  
Search Methods ◽  
Swarm Optimization ◽  
Cpu Time ◽  
Local Search Methods

In this paper we investigate the use of two types of local search methods (LSM), the Simulated Annealing (SA) and Particle Swarm Optimization (PSO), to solve the problems ( ) and . The results of the two LSMs are compared with the Branch and Bound method and good heuristic methods. This work shows the good performance of SA and PSO compared with the exact and heuristic methods in terms of best solutions and CPU time.

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