Uncertain optimization (with a special focus on data envelopment analysis)
Küçük Resim Yok
Tarih
2024
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Uncertain optimization refers to contexts where there is uncertainty in models and data. It potentially has various applications in different domains such as portfolio selection, inventory management, pollution reduction, sustainable development, resource allocation and reallocation, and performance analysis. In real life, decisions often need to be made under unknown scenarios. In our terminology, uncertainty refers to the variability of data and optimization refers to the analysis and solution of a problem that involves optimizing an objective, given a set of constraints. This chapter deals with uncertain optimization problems with a special emphasis on data envelopment analysis (DEA). Since many books discuss fuzzy optimization problems, only the stochastic type of uncertainty in data and models is considered here.
Açıklama
Anahtar Kelimeler
DEA, Measure, Optimization, Uncertainty
Kaynak
Decision-making models: a perspective of fuzzy logic and machine learning
WoS Q Değeri
Scopus Q Değeri
Cilt
Sayı
Künye
Amirteimoori, A., Allahviranloo, T., & Shahriari, M. (2024). Uncertain optimization (with a special focus on data envelopment analysis). In Decision-Making Models (pp. 453-464). Academic Press.
