multistage stochastic programming is a key technology for making decisions over time in an uncertain environment. one of the promising areas in which this technology is implementable, is medium term planning of electricity production and trading where decision makers are typically faced with uncertain parameters (such as future demands and market prices) that can be described by stochastic proc...

 We consider a generalization of the classical quadratic assignment problem, where coordinates of locations are uncertain and only upper and lower bounds are known for each coordinate. We develop a mixed integer linear programming model as a robust counterpart of the proposed uncertain model. A key challenge is that, since the uncertain model involves nonlinear objective function of the ...

Development of every society is incumbent upon energy sector’s technological and economic effectiveness. The electricity industry is a growing and needs to have a better performance to effectively cover the demand. The industry requires a balance between cost and efficiency through careful design and planning. In this paper, a two-stage stochastic programming model is presented for the design o...

Multistage stochastic programming is a key technology for making decisions over time in an uncertain environment. One of the promising areas in which this technology is implementable, is medium term planning of electricity production and trading where decision makers are typically faced with uncertain parameters (such as future demands and market prices) that can be described by stochastic proc...

In order to catch up with reality, all the macro-decisions related to long-term mining production planning must be made simultaneously and under uncertain conditions of determinant parameters. By taking advantage of the chance-constrained programming, this paper presents a stochastic model to create an optimal strategy for producing bimetallic deposit open-pit mines under certain and uncertain ...

This paper deals with a realistic multi-period liner ship fleet planning problem by incorporating stochastic dependency of the random and period-dependent container shipment demand. This problem is formulated as a multi-period stochastic programming model with a sequence of interrelated two-stage stochastic programming (2SSP) problems characterized ship fleet planning in each single period. A s...

This paper presents a stochastic optimization model and efficient decomposition algorithm for multi-site capacity planning under the uncertainty of the TFT-LCD industry. The objective of the stochastic capacity planning is to determine a robust capacity allocation and expansion policy hedged against demand uncertainties because the demand forecasts faced by TFT-LCD manufacturers are usually ina...

Cell formation (CF) problem is one of the most important decision problems in designing a cellular manufacturing system includes grouping machines into machine cells and parts into part families. Several factors should be considered in a cell formation problem. In this work, robust optimization of a mathematical model of a dynamic cell formation problem integrating CF, production planning and w...

This paper presents a new bi-level multi-objective model to valorize the microgrid (MG) flexibility based on flexible power management system. It considers presence of renewable and resources including demand response program (DRP), energy storage system integrated unit electric spring with vehicles (EVs) parking (IUEE). The proposed in upper-level maximizes expected profit subject constraints....