On multi-criteria chance-constrained capacitated single-source discrete facility location problems
| Autor: | Ömer Burak Kınay, Francisco Saldanha-da-Gama, Bahar Y. Kara |
|---|---|
| Přispěvatelé: | Kara, Bahar Y. |
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Mathematical optimization Chance-constraints 021103 operations research Information Systems and Management Humanitarian Logistics Computer science Multi-criteria optimization Strategy and Management 0211 other engineering and technologies Probabilistic logic Context (language use) 02 engineering and technology Management Science and Operations Research Humanitarian logistics Facility location problem Discrete facility location Set (abstract data type) Single-sourcing 020901 industrial engineering & automation Goal programming Service level Throughput (business) |
| Zdroj: | Omega |
| ISSN: | 0305-0483 |
| DOI: | 10.1016/j.omega.2018.02.007 |
| Popis: | This work aims at investigating multi-criteria modeling frameworks for discrete stochastic facility location problems with single sourcing. We assume that demand is stochastic and also that a service level is imposed. This situation is modeled using a set of probabilistic constraints. We also consider a minimum throughput at the facilities to justify opening them. We investigate two paradigms in terms of multi-criteria optimization: vectorial optimization and goal programming. Additionally, we discuss the joint use of objective functions that are relevant in the context of some humanitarian logistics problems. We apply the general modeling frameworks proposed to the so-called stochastic shelter site location problem. This is a problem emerging in the context of preventive disaster management. We test the models proposed using two real benchmark data sets. The results show that considering uncertainty and multiple objectives in the type of facility location problems investigated leads to solutions that may better support decision making. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect