Double layer ACO algorithm for the multi-objective FJSSP
type: Item
instance of: scholarly article
title: Double layer ACO algorithm for the multi-objective FJSSP
zbMATH Open document ID: 1175.90201
author: Lining Xing
author: Ke-Wei Yang
author: Yingwu Chen
published in: New Generation Computing
publication date: 2009-10-09T00:00:00Z
Mathematics Subject Classification ID: 90B35
Mathematics Subject Classification ID: 90C27
Mathematics Subject Classification ID: 90C29
zbMATH DE Number: 5612698
zbMATH Keywords: combinatorial optimization
zbMATH Keywords: ant colony optimization
zbMATH Keywords: multi-objective optimization
zbMATH Keywords: flexible job shop scheduling
zbMATH Keywords: scheduling knowledge
MaRDI profile type: Publication
full work available at URL: s00354-008-0048-6
OpenAlex ID: W2013720120
cites work: Some new results on simulated annealing applied to the job shop scheduling problem
cites work: A tabu search method guided by shifting bottleneck for the job shop scheduling problem
cites work: An efficient genetic algorithm for job shop scheduling with tardiness objectives.
cites work: A hybrid genetic algorithm for the job shop scheduling problem
cites work: Ant colony optimization combined with taboo search for the job shop scheduling problem
cites work: An alternative framework to Lagrangian relaxation approach for job shop scheduling.
cites work: A structural design of decision support systems for deteriorating repairable systems.
cites work: Approximation schemes for job shop scheduling problems with controllable processing times
cites work: Job-shop scheduling with multi-purpose machines
cites work: Routing and scheduling in a flexible job shop by tabu search
cites work: Pareto-optimality approach for flexible job-shop scheduling problems: Hybridization of evolutionary algorithms and fuzzy logic
cites work: Tabu search for the job-shop scheduling problem with multi-purpose machines
cites work: Effective neighbourhood functions for the flexible job shop problem
cites work: An integrated approach for modeling and solving the general multiprocessor job-shop scheduling problem using tabu search
cites work: Quantifiers in the formulation of multiple objective decision functions
cites work: Q5480099
cites work: An effective architecture for learning and evolving flexible job-shop schedules
DOI: 10.1007/S00354-008-0048-6
description: scientific article; zbMATH DE number 5612698