2,046 research outputs found
Fuzzy Random Noncooperative Two-level Linear Programming through Absolute Deviation Minimization Using Possibility and Necessity
This paper considers fuzzy random two-level linear programming problems under noncooperative behaviorof the decision makers. Having introduced fuzzy goals of decision makers together with the possibiliy and necessity measure, following absolute deviation minimization, fuzzy random two-level programin problems are transformed into deterministic ones. Extended Stackelberg solutions are introduced andcomputational methods are also presented
A McKean-Vlasov approach to distributed electricity generation development
This paper analyses the interaction between centralised carbon emissive
technologies and distributed intermittent non-emissive technologies. In our
model, there is a representative consumer who can satisfy her electricity
demand by investing in distributed generation (solar panels) and by buying
power from a centralised firm at a price the firm sets. Distributed generation
is intermittent and induces an externality cost to the consumer. The firm
provides non-random electricity generation subject to a carbon tax and to
transmission costs. The objective of the consumer is to satisfy her demand
while mini\-mising investment costs, payments to the firm and intermittency
costs. The objective of the firm is to satisfy the consumer's residual demand
while minimising investment costs, demand deviation costs, and maximising the
payments from the consumer. We formulate the investment decisions as
McKean-Vlasov control problems with stochastic coefficients. We provide
explicit, price model-free solutions to the optimal decision problems faced by
each player, the solution of the Pareto optimum, and the Stackelberg
equilibrium where the firm is the leader. We find that, from the social
planner's point of view, the carbon tax or transmission costs are necessary to
justify a positive share of distributed capacity in the long-term, whatever the
respective investment costs of both technologies are. The Stackelberg
equilibrium is far from the Pareto equilibrium and leads to an over-investment
in distributed energy and to a much higher price for centralised energy
Quantitative analysis of multi-periodic supply chain contracts with options via stochastic programming
We propose a stochastic programming approach for quantitative analysis of supply contracts, involving flexibility, between a buyer and a supplier, in a supply chain framework. Specifically, we consider the case of multi-periodic contracts in the face of correlated demands. To design such contracts, one has to estimate the savings or costs induced for both parties, as well as the optimal orders and commitments. We show how to model the stochastic process of the demand and the decision problem for both parties using the algebraic modeling language AMPL. The resulting linear programs are solved with a commercial linear programming solver; we compute the economic performance of these contracts, giving evidence that this methodology allows to gain insight into realistic problems.stochastic programming; supply contract; linear programming; modeling software; decision tree
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