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Solving the multiple level warehouse layout problem using ant colony optimization
- Publication Year :
- 2019
- Publisher :
- Springer Verlag, 2019.
-
Abstract
- This paper addresses the multiple level warehouse layout problem, which involves assigning items to cells and levels with the objective of minimizing transportation costs. A monthly demand and an inventory requirement are associated with every item type along with vertical and horizontal unit transportation costs. The warehouse has one port to transport items vertically from ground floor to the other levels, where each item must be assigned to exactly one cell on the assigned level. An ant colony optimization (ACO) algorithm is adapted to this NP-complete problem and its performance is evaluated by comparing its solutions to the ones obtained using genetic algorithms (GA) as well as the optimal solutions for small problems. The computational results reflected the superiority of ACO in large-size problem instances, with a marginally better performance than GA in smaller ones, while solving the tested instances within a reasonable computational time. Furthermore, ACO was able to attain most of the known optimal solutions for small-size problem instances. Publisher's Version
- Subjects :
- 0209 industrial biotechnology
Mathematical optimization
Multiple level warehouse layout problem
Computer science
Strategy and Management
0211 other engineering and technologies
Computational intelligence
Metaheuristic
02 engineering and technology
Management Science and Operations Research
Ant colony optimization
020901 industrial engineering & automation
Storage (materials)
Management of Technology and Innovation
Numerical Analysis
021103 operations research
Ant colony optimization algorithms
Port (computer networking)
Warehouse
Storage material
Computational Theory and Mathematics
Modeling and Simulation
Storage assignment
Ground floor
Statistics, Probability and Uncertainty
Warehouses
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....f521cb3651fa05d27bd8d367a3180f93