| Autor: |
Laura Cruz-Reyes, Christian Ayala-Esquivel, José Francisco Delgado-Orta, Alejandro Palacios-Espinosa |
| Rok vydání: |
2015 |
| Předmět: |
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| Zdroj: |
Research in Computing Science. 104:41-50 |
| ISSN: |
1870-4069 |
| DOI: |
10.13053/rcs-104-1-3 |
| Popis: |
In this paper the Purchasing Scheduling Problem (PSP) with limited funds is presented. PSP is formulated through the optimization of two objectives based on the inventory-supply process: maximization of satisfied demands and minimization of purchasing costs. The problem is solved using two variants of the Ant Colony System algorithm (ACS), designed under Pareto's optimization principle in which elements of multi-objective representation for computing a feasible solution are incorporated to the basic design of ACS. Experimental results reveal that the Pareto approach improves solutions over the ACS in 8%, obtaining an efficiency of 80% solving the set of PSP instances as purchasing plans. This reveals the advantages of developing evolutionary algorithms based on multi-objective approaches, which can be exploited in planning and scheduling systems. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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