In this research, we integrate the issues related to operations and marketing strategy of firms characterized by large product variety, short lead times, and demand variability in an assemble-to-order environment. The operations decisions are the inventory level of components and semi-finished...

Large corporations fund their capital and operational expenses by issuing bonds with a variety of indexations, denominations, maturities and amortization schedules. We propose a multistage linear stochastic programming model that optimizes bond issuance by minimizing the mean funding cost while...

This article analyzes the fleet management problem faced by a firm when deciding which vehicles to add to its fleet. Such a decision depends not only on the expected mileage and tasks to be assigned to the vehicle but also on the evolution of fuel and CO2 emission prices and on fuel efficiency....

Traditionally, two variants of the L-shaped method based on Benders’ decomposition principle are used to solve two-stage stochastic programming problems: the aggregate and the disaggregate version. In this study we report our experiments with a special convex programming method applied to the...

This article presents a stochastic dynamic Generalized Nash-Cournot model to describe the evolution of the natural gas markets. The major gas chain players are depicted including: producers, consumers, storage, and pipeline operators, as well as intermediate local traders. Our economic structure...

This paper explores the impacts of long-term technology and climate uncertainties on the optimal evolution of the World energy system. Stochastic programming with the TIAM-World model is used for a parametric analysis of hedging strategies, varying the probabilities associated to each of two...

A virtual power plant aggregates various local production/consumption units that act in the market as a single entity. This paper considers a virtual power plant consisting of an intermittent source, a storage facility, and a dispatchable power plant. The virtual power plant sells and purchases...

In this study, a new Pseudo-optimal Inexact Stochastic Interval Type-2 Fuzzy Sets Linear Programming (PIS-IT2FSLP) energy model is developed to support energy system planning and environment requirements under uncertainties for Xiamen City. The PIS-IT2FSLP model is based on an integration of...

In this paper we consider characterizations of the robust uncertainty sets associated with coherent and distortion risk measures. In this context we show that if we are willing to enforce the coherent or distortion axioms only on random variables that are affine or linear functions of the vector...

Uncertainty in biomass supply is a critical issue that needs to be considered in the production planning of bioenergy plants. Incorporating uncertainty in supply chain planning models provides improved and stable solutions. In this paper, we first reformulate a previously developed non-linear...