Multi-objective Variable Neighborhood Search Algorithms for a Single Machine Scheduling Problem with Distinct due Windows

Authors:
José Elias Claudio Arroyo;Rafael dos Santos Ottoni;Alcione de Paiva Oliveira
Affiliations:
Departamento de Informática, Universidade Federal de Viçosa, Viçosa - MG - Brazil;Departamento de Informática, Universidade Federal de Viçosa, Viçosa - MG - Brazil;Departamento de Informática, Universidade Federal de Viçosa, Viçosa - MG - Brazil
Venue:
Electronic Notes in Theoretical Computer Science (ENTCS)
Year:
2011

Citing 13
Cited 2

Sequencing with earliness and tardiness penalties: a review

Operations Research
Minimizing total tardiness on one machine is NP-hard

Mathematics of Operations Research
A genetic algorithm for job sequencing problems with distinct due dates and general early-tardy penalty weights

Computers and Operations Research
Variable neighborhood search

Computers and Operations Research
Minimizing total earliness and tardiness on a single machine using a hybrid heuristic

Computers and Operations Research
A variable neighborhood search for minimizing single machine weighted earliness and tardiness with common due date

Computers and Industrial Engineering
Minimizing earliness-tardiness penalties for common due date single-machine scheduling problems by a recovering beam search algorithm

Computers and Industrial Engineering
Minimizing the makespan in a single machine scheduling problem with a time-based learning effect

Information Processing Letters
An adaptive genetic algorithm for solving the single machine scheduling problem with earliness and tardiness penalties

SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Multi-objective redundancy allocation optimization using a variable neighborhood search algorithm

Journal of Heuristics
1984-2004 – 20 years of multiobjective metaheuristics. but what about the solution of combinatorial problems with multiple objectives?

EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Performance assessment of multiobjective optimizers: an analysis and review

IEEE Transactions on Evolutionary Computation
Balance between genetic search and local search in memetic algorithms for multiobjective permutation flowshop scheduling

IEEE Transactions on Evolutionary Computation

Multi-objective metaheuristic algorithms for the resource-constrained project scheduling problem with precedence relations

Computers and Operations Research
Hybrid GRASP Heuristics to Solve an Unrelated Parallel Machine Scheduling Problem with Earliness and Tardiness Penalties

Electronic Notes in Theoretical Computer Science (ENTCS)

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we compare three multi-objective algorithms based on Variable Neighborhood Search (VNS) heuristic. The algorithms are applied to solve the single machine scheduling problem with sequence dependent setup times and distinct due windows. In this problem, we consider minimizing the total weighted earliness/tardiness and the total flowtime criteria. We introduce two intensification procedures to improve a multi-objective VNS (MOVNS) algorithm proposed in the literature. The performance of the algorithms is tested on a set of medium and larger instances of the problem. The computational results show that the proposed algorithms outperform the original MOVNS algorithm in terms of solution quality. A statistical analysis is conducted in order to analyze the performance of the proposed methods.