A constraint programming model for the scheduling of JIT cross-docking systems with preemption

In this paper, a scheduling problem of minimizing the total of the earliness, tardiness and the number of preemption for the outbound trucks on a cross-dock system is considered. This problem, which is known to be NP-hard, is compatible with the concepts of just-in-time (JIT) production and supply c...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Journal of intelligent manufacturing Ročník 27; číslo 2; s. 297 - 313
Hlavní autoři: Fazel Zarandi, M. H., Khorshidian, H., Akbarpour Shirazi, M.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.04.2016
Springer Nature B.V
Témata:
Advanced manufacturing technologies
Business and Management
Chains
Compatibility
Control
Docking
Experiments
Genetic algorithms
Integer programming
Just in time
Logistics
Machines
Management
Manufacturing
Mathematical models
Mechatronics
Multiple criterion
Nonlinearity
Processes
Production
Production scheduling
Robotics
Scheduling
Studies
Supply chain management
Trucks
Just-in-time scheduling
Preemption
Constraint satisfaction problem
Genetic algorithm
Cross-docking system
ISSN:0956-5515, 1572-8145
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:In this paper, a scheduling problem of minimizing the total of the earliness, tardiness and the number of preemption for the outbound trucks on a cross-dock system is considered. This problem, which is known to be NP-hard, is compatible with the concepts of just-in-time (JIT) production and supply chain management. A new multi-criteria model, with non-linear terms and integer variables, which cannot be solved efficiently for large sized problems, is proposed. This paper also shows how to map a JIT cross-dock model to a constraint satisfaction problem (CSP) and integer programming (IP). To solve the model for real size applications, a genetic algorithm (GA) is applied. Finally, a computational experiment is carried out to analyze the performances of CSP, GA and IP models with respect to modeling capability, solution quality and time.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0956-5515
1572-8145
DOI:10.1007/s10845-013-0860-9