Genetic algorithms for task assignments in logistic warehouses
| Autor: | Zhaodong Wu, Min Wang |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Java
Computer science business.industry P versus NP problem Machine learning computer.software_genre Warehouse Scheduling (computing) Multi objective model Genetic algorithm Artificial intelligence General Agricultural and Biological Sciences business Assignment problem computer computer.programming_language |
| Zdroj: | International Journal of Modelling in Operations Management. 7:196 |
| ISSN: | 2042-4108 2042-4094 |
| DOI: | 10.1504/ijmom.2019.103036 |
| Popis: | By analysing the relevant elements in the allocation of storage tasks, a multi-objective storage task assignment model was built considering time and resource indicators and an improved genetic algorithm for this model is given and analysed through a case study. To assist warehouse managers in task scheduling, a desktop application for the storage task assignment was written in Java. The results showed that the improved genetic algorithm could accelerate the convergence speed and this model makes corresponding adjustments while the actual situation of the storage task changes. Compared with the task assignment scheme made through experience, the model not only reduces the time required but also the resources used. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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