Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/287608 
Year of Publication: 
2021
Citation: 
[Journal:] Operations Research Forum [ISSN:] 2662-2556 [Volume:] 2 [Issue:] 3 [Publisher:] Springer International Publishing [Place:] Cham [Year:] 2021
Publisher: 
Springer International Publishing, Cham
Abstract: 
The distribution/allocation problem is known as one of the most comprehensive strategic decision. In real-world cases, it is impossible to solve a distribution/allocation problem in traditional ways with acceptable time. Hence researchers develop efficient non-traditional techniques for the large-term operation of the whole supply chain. These techniques provide near optimal solutions particularly for large-scale test problems. This paper presents an integrated supply chain model which is flexible in the delivery path. As the solution methodology, we apply a memetic algorithm with a neighborhood search mechanism and novelty in population presentation method called "extended random path direct encoding method." To illustrate the performance of the proposed memetic algorithm, LINGO optimization software serves as comparison basis for small size problems. In large-size cases that we are dealing with in real world, a classical genetic algorithm as the second metaheuristic algorithm is considered to compare the results and show the efficiency of the memetic algorithm.
Subjects: 
Integrated logistics network
Flexible path
Memetic algorithm
Genetic algorithm
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.