| Autor: |
Yacouba Adama Koné, Jacqueline Konaté, Oumar Y. Maïga, Hamidou Tembiné |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
Algorithms, Vol 13, Iss 11, p 270 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
1999-4893 |
| DOI: |
10.3390/a13110270 |
| Popis: |
Strategic modelling with a panoramic view plays an important role in decision-making problems. It offers the possibility of generating different solutions before making a decision. This is particularly relevant in critical situations. This article addresses the problem of allocating resources, whether financial, material or human, so that it is optimal under a given set of constraints and inter-dependencies with other systems. To do this, existing strategies such as those of Colonel Blotto are studied in order to evaluate them according to some criteria, including the heterogeneity or homogeneity of resources and/or battlefields. Based on the results of these configurations, we propose distributed strategic learning methods to find better resource allocation strategies. The proposed algorithms are implemented under various scenarios, including incomplete information. Case studies are carried out to test the effectiveness of these new strategies compared to previous ones. A complexity analysis of the different algorithms is also presented. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
|
Nepřihlášeným uživatelům se plný text nezobrazuje |
K zobrazení výsledku je třeba se přihlásit.
|
