Journal ArticleDOI
A resource-constrained assembly job shop scheduling problem with Lot Streaming technique
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TLDR
For the first time, the application of Lot Streaming technique is extended to a Resource-Constrained Assembly Job Shop Scheduling Problem (RC_AJSSP) and an innovative approach with Genetic Algorithm (GA) is proposed.About:
This article is published in Computers & Industrial Engineering.The article was published on 2009-10-01. It has received 67 citations till now. The article focuses on the topics: Flow shop scheduling & Job shop scheduling.read more
Citations
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Journal ArticleDOI
A research survey: review of AI solution strategies of job shop scheduling problem
Banu Çaliş,Serol Bulkan +1 more
TL;DR: This paper focus on artificial intelligence approaches to NP-hard job shop scheduling (JSS) problem and successful approaches of artificial intelligence techniques such as neural network, genetic algorithm, multi agent systems, simulating annealing, bee colony optimization, ant colony optimization and particle swarm algorithm are presented.
Journal ArticleDOI
IFSJSP: A novel methodology for the Job-Shop Scheduling Problem based on intuitionistic fuzzy sets
TL;DR: In this article, a method to address the job shop scheduling problem under an uncertain environment based on Intuitionistic Fuzzy Sets (IFS) is presented. But the method is not suitable for the case where the uncertain information in the JSP is transferred to the IFS.
Journal ArticleDOI
Deterministic assembly scheduling problems: A review and classification of concurrent-type scheduling models and solution procedures
TL;DR: This paper proposes a unified notation for assembly scheduling models that encompass all concurrent-type scheduling problems, and uses this notation, the existing contributions are reviewed and classified into a single framework so a comprehensive, unified picture of the field is obtained.
Journal ArticleDOI
A distributed heterogeneous permutation flowshop scheduling problem with lot-streaming and carryover sequence-dependent setup time
TL;DR: An enhanced artificial bee colony algorithm (NEABC) with strong intensification is proposed to generate promising swarm and a restart strategy is designed in the scout bee stage with the consideration of the special onlooker bee stage of the algorithm.
Journal ArticleDOI
A simulation-based study of dispatching rules in a dynamic job shop scheduling problem with batch release and extended technical precedence constraints
TL;DR: A simulation-based analysis of dispatching rules for scheduling in a dynamic job shop with batch release taking into account the extended technical precedence constraint is considered, showing that for minimizing the total tardiness and the percentage of tardy jobs, the four new proposed dispatches are very effective under relatively loose due date.
References
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Book
Adaptation in natural and artificial systems
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Proceedings ArticleDOI
A new optimizer using particle swarm theory
TL;DR: The optimization of nonlinear functions using particle swarm methodology is described and implementations of two paradigms are discussed and compared, including a recently developed locally oriented paradigm.
Journal ArticleDOI
A particle swarm optimization algorithm for makespan and total flowtime minimization in the permutation flowshop sequencing problem
TL;DR: A heuristic rule called the smallest position value (SPV) borrowed from the random key representation of Bean was developed to enable the continuous particle swarm optimization algorithm to be applied to all classes of sequencing problems.
Journal ArticleDOI
A discrete version of particle swarm optimization for flowshop scheduling problems
TL;DR: A PSO algorithm, extended from discrete PSO, for flowshop scheduling, which incorporates a local search scheme into the proposed algorithm, called PSO-LS, and shows that the local search can be really guided by PSO in the approach.
Journal ArticleDOI
A hybrid particle swarm optimization for job shop scheduling problem
D. Y. Sha,Cheng-Yu Hsu +1 more
TL;DR: A hybrid particle swarm optimization (PSO) for the job shop problem (JSP) is proposed and the computational results show that the modified PSO performs better than the original design, and that the hybrid PSO is better than other traditional metaheuristics.