A two-stage inexact-stochastic programming model for planning carbon dioxide emission trading under uncertainty
نویسندگان
چکیده
In this study, a two-stage inexact-stochastic programming (TISP) method is developed for planning carbon dioxide (CO2) emission trading under uncertainty. The developed TISP incorporates techniques of interval-parameter programming (IPP) and two-stage stochastic programming (TSP) within a general optimization framework. The TISP can not only tackle uncertainties expressed as probabilistic distributions and discrete intervals, but also provide an effective linkage between the pre-regulated greenhouse gas (GHG) management policies and the associated economic implications. The developed method is applied to a case study of energy systems and CO2 emission trading planning under uncertainty. The results indicate that reasonable solutions have been generated. They can be used for generating decision alternatives and thus help decision makers identify desired GHG abatement policies under various economic and system-reliability constraints. 2009 Elsevier Ltd. All rights reserved.
منابع مشابه
Global Supply Chain Management under Carbon Emission Trading Program Using Mixed Integer Programming and Genetic Algorithm
In this paper, the transportation problem under the carbon emission trading program ismodelled by mathematical programming and genetic algorithm. Since green supply chain issuesbecome important and new legislations are taken into account, carbon emissions costs are included inthe total costs of the supply chain. The optimisation model has the ability to minimise the total costsand provides the ...
متن کاملA Stochastic Programming Approach for a Multi-Site Supply Chain Planning in Textile and Apparel Industry under Demand Uncertainty
In this study, a new stochastic model is proposed to deal with a multi-product, multi-period, multi-stage, multi-site production and transportation supply chain planning problem under demand uncertainty. A two-stage stochastic linear programming approach is used to maximize the expected profit. Decisions such as the production amount, the inventory level of finished and semi-finished product, t...
متن کاملIntegrated Inspection Planning and Preventive Maintenance for a Markov Deteriorating System Under Scenario-based Demand Uncertainty
In this paper, a single-product, single-machine system under Markovian deterioration of machine condition and demand uncertainty is studied. The objective is to find the optimal intervals for inspection and preventive maintenance activities in a condition-based maintenance planning with discrete monitoring framework. At first, a stochastic dynamic programming model whose state variable is the ...
متن کاملTwo-stage Stochastic Programing Based on the Accelerated Benders Decomposition for Designing Power Network Design under Uncertainty
In this paper, a comprehensive mathematical model for designing an electric power supply chain network via considering preventive maintenance under risk of network failures is proposed. The risk of capacity disruption of the distribution network is handled via using a two-stage stochastic programming as a framework for modeling the optimization problem. An applied method of planning for the net...
متن کاملA queuing-location model for in multi-product supply chain with lead time under uncertainty
Supply chain network design (SCND) problem has recently been gaining attention because an integrated management of the supply chain (SC) can reduce the unexpected/undesirable events and can affect definitely the efficiency of all the chain. A critical component of the planning activities of a manufacturing firm is the efficient design of its SC. Hence, SCND affords a sensitive platform for effi...
متن کامل