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3299. Stochastic Dynamic Cost-Efficiency: Development of a Chance-Constrained Data Envelopment Analysis (CCDEA) model with Window Analysis and Optimal Control Principles
Invited abstract in session MC-48: DEA and stochastic models, stream Data Envelopment Analysis and its Application.
Monday, 12:30-14:00Room: 60 (building: 324)
Authors (first author is the speaker)
| 1. | Paulo Nocera Alves Junior
|
| Universidad Católica del Norte (UCN), Escuela de Ingeniería de Coquimbo (EIC) | |
| 2. | Ali Emrouznejad
|
| Surrey Business School, University of Surrey | |
| 3. | Wilfredo Yushimito
|
| Universidad Adolfo Ibáñez (UAI) | |
| 4. | Carlos Monardes
|
| School of Engineering, Universidad Católica del Norte | |
| 5. | Isotilia Costa Melo
|
| ICN Business School |
Abstract
This study presents the development of an innovative approach to Stochastic Data Envelopment Analysis (SDEA), considering Chance-Constrained Programming (CCP), Window Analysis (WA), and Optimal Control Theory (OCT) principles in a framework with time and probabilistic constraints. Besids, it involves the average values, covariance matrices and probabilities of each window over time. By incorporating dynamic elements from recent advancements, such as intermediate variables (inventory costs), this model examines the total cost efficiency based on the relationship among variables, such as costs of goods sold (related to the demand), costs of purchased (or produced) products (related to the production or ordered quantities), and inventory costs (related to the initial and final inventories of the period), along with their uncertainties. This enables a dynamic and stochastic evaluation of the cost efficiency of inventory control systems. OCT principles are applied to link variables and introduce dynamics into the system, whereas CCP and WA are utilized to construct temporal windows and integrate their stochastic properties. The result is an SDEA model grounded in OCT principles to assess the total cost efficiency of the control systems from Decision-Making Units (DMUs), as in the retail sector, over time and considering uncertainties. This approach considers real-world conditions, thereby improving analysis and contributing to the development of more efficient control systems.
Keywords
- Data Envelopment Analysis
- Programming, Stochastic
- Optimal Control
Status: accepted
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