Topic
Stochastic programming
About: Stochastic programming is a research topic. Over the lifetime, 12343 publications have been published within this topic receiving 421049 citations.
Papers published on a yearly basis
Papers
More filters
••
TL;DR: A dynamic stochastic integer programming model for the single airport ground holding problem, in which ground delays assigned to flights can be revised during different decision stages, based on weather forecasts, makes it applicable under the collaborative decision making (CDM) paradigm.
Abstract: In this paper, we present a dynamic stochastic integer programming (IP) model for the single airport ground holding problem, in which ground delays assigned to flights can be revised during different decision stages, based on weather forecasts. The performance gain from our model is particularly significant in the following cases: (1) under stringent ground holding policy, (2) when an early ground delay program (GDP) cancellation is likely, and (3) for airports where the ratio between adverse and fair weather capacities is lower. The choice of ground delay cost component in the objective function strongly affects the allocation policy. When it is linear, the optimal solution involves releasing the long-haul flights at or near their scheduled departure times and using the short-haul flights to absorb delays if low-capacity scenarios eventuate. This policy resembles the current practice of exempting long-distance flights during ground delay programs. For certain convex ground delay cost functions, the spread of ground delay is more or less uniform across all categories of flights, which makes the overall delay assignment more equitable. Finally, we also present a methodology that could enable intra-airline flight substitutions by airlines after our model has been executed and scenario-specific slots have been assigned to all flights, and hence to the airlines that operate them. This makes our model applicable under the collaborative decision making (CDM) paradigm by allowing airlines to perform cancellations and substitutions and hence reoptimize their internal delay cost functions.
131 citations
••
TL;DR: In this paper, the authors investigate the asymptotic behavior of estimators of the optimal value and optimal solutions of a stochastic program and show that in the presence of inequality constraints, the estimators are not normal in general.
Abstract: The aim of this article is to investigate the asymptotic behaviour of estimators of the optimal value and optimal solutions of a stochastic program. These estimators are closely related to the $M$-estimators introduced by Huber (1964). The parameter set of feasible solutions is supposed to be defined by a number of equality and inequality constraints. It will be shown that in the presence of inequality constraints the estimators are not asymptotically normal in general. Maximum likelihood and robust regression methods will be discussed as examples.
131 citations
••
TL;DR: This work examines and compares simulation-based algorithms for solving the agent scheduling problem in a multiskill call center and proposes a solution approach that combines simulation with integer or linear programming, with cut generation.
131 citations
••
TL;DR: In this paper, a generic reverse logistics network design model under return quantity, sorting ratio (quality), and transportation cost uncertainties is proposed to maximize profit of a third party waste of electrical and electronic equipment recycling companies.
Abstract: In recent years, Reverse Logistics has received increasing attentions in supply chain management area. The reasons such as political, economic, green image and social responsibility etc. force firms to develop strategies to their current systems. The aim of this study is to propose a generic Reverse Logistics Network Design model under return quantity, sorting ratio (quality), and transportation cost uncertainties. We present a generic multi-echelon, multi-product and capacity constrained two stage stochastic programing model to take into consideration uncertainties in Reverse Logistics Network Design for a third party waste of electrical and electronic equipment recycling companies to maximize profit. We validated developed model by applying to a real world case study for waste of electrical and electronic equipment recycling firm in Turkey. Sample average approximation method was used to solve the model. Results show that the developed two stage stochastic programming model provides acceptable solutions to make efficient decisions under quantity, quality and transportation cost uncertainties.
131 citations
••
TL;DR: In this article, a two-stage stochastic programming (SP) model and a chance-constrained programming (CCP) model are developed to determine a minimal set of suppliers and optimal order quantities with consideration of business volume discounts.
131 citations