Results 41 to 50 of about 73,476 (218)

Is AI an Algorithm by Any Other Name? Behavioral Reactions to AI‐ and Model‐Based Demand Planning Algorithms

open access: yesJournal of Operations Management, EarlyView.
ABSTRACT With the ongoing deployment of AI algorithms, managers do not know whether existing demand planning processes account for possible differences in human behavior when using AI‐based systems in comparison to legacy model‐based systems. This study examines how human behavior may differ when performing demand forecasting tasks due to the ...
Finnegan McKinley   +3 more
wiley   +1 more source

Bridging the implementation gap in MCABC inventory management: from a taxonomy to practical archetypes

open access: yesInternational Transactions in Operational Research, EarlyView.
Abstract Despite increasing demands for resilient and sustainable supply chains, inventory management often relies on outdated single‐criterion analyses. While multi‐criteria ABC (MCABC) analyses provide a theoretically mature assessment of resilience‐sustainability‐benefit trade‐offs in inventory, their adoption remains limited due to fragmented ...
Lukas Grützner, Michael H. Breitner
wiley   +1 more source

A Multiattribute Utility Approach to Target Assignment

open access: yes, 2009
This paper introduces the multiattribute utility theory to the control Lyapunov function design framework. As an illustration we focus on the problem of multi-target assignment.
Xi Chen   +2 more
core   +1 more source

Extended Utility and DEA Models without Explicit Input [PDF]

open access: yes, 2013
In this paper, we discuss the relationship between multi-attribute utility theory and data envelopment analysis (DEA) models without explicit inputs (DEA-WEI), including dual models and some theoretical analysis of DEA-WEI models. We then propose generic
Wanfang Shen   +7 more
core   +1 more source

Additive utility in prospect theory [PDF]

open access: yes, 2008
Prospect theory is currently the main descriptive theory of decision under uncertainty. It generalizes expected utility by introducing nonlinear decision weighting and loss aversion.
Zank, Horst; id_orcid   +8 more
core   +3 more sources

Multiattribute Utility Analysis: A Brief Survey

open access: yes, 1975
The role of multiattribute utility theory is first placed in the overall context of decision analysis. Then an approach that has proven useful in adapting the theory to be a practical tool is illustrated.
Keeney, R.L., Ralph L. Keeney
core   +1 more source

MULTIATTRIBUTE UTILITY THEORY, MULTIPLE OBJECTIVES AND UNCERTAINTY IN EX ANTE PROJECT EVALUATION [PDF]

open access: yes, 2017
A wide variety of methods have been suggested for ex ante project appraisal. The most logical and complete of these appears to be multiattribute utility theory (MAUT) which provides a formal procedure for handling the difficulties of ex ante evaluation ...
Dillon, John L., Perry, Chad
core   +1 more source

Risk Assessment and Emergency Decision‐Support for Urban Transportation Network Subjected to Seismic Hazards Using a Bayesian Network

open access: yesJournal of Advanced Transportation, Volume 2026, Issue 1, 2026.
The assessment of the risk associated with urban road networks, particularly in the context of earthquakes, is of paramount importance for the identification and reinforcement of the most vulnerable sections of urban road networks and the selection of optimal emergency rescue routes.
Binyang Xu, Indrajit Ghosh
wiley   +1 more source

Heterogeneous Methodology to Support the Early Diagnosis of Gestational Diabetes

open access: yesIEEE Access, 2019
Gestational diabetes mellitus (GDM) is a public health problem. Along with changes in eating habits, increased purchasing power, and climate change, among others, the number of women with gestational diabetes complicated by pregnancy is increasing.
Egidio Gomes Filho   +4 more
doaj   +1 more source

A Multistage Two‐Sided Matching Model in Interval‐Valued Triangular Fuzzy Environments

open access: yesComplexity, Volume 2026, Issue 1, 2026.
In two‐sided matching problems, accurately quantifying preference intensity using precise numerical values remains a significant challenge due to the inherent complexity and fuzziness of real‐world decision‐making. Moreover, existing research rarely considers the staged dynamics of matching processes across multiple time periods. To address these gaps,
Jian-min Qiao   +3 more
wiley   +1 more source

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