In this paper, we propose an algorithm base on decomposition technique for solvingthe mixed integer linear multiplicative-linear bilevel problems. In actuality, this al-gorithm is an application of the algorithm given by G. K. Saharidis et al for casethat the rst level objective function is linear multiplicative. We use properties ofquasi-concave of bilevel programming problems and decompose th...

Electricity demand is forecasted to double in 2035, and it is vital to address the economicsof electrical energy generation for planning purposes. This study aims to examine the applicability ofGravitational Search Algorithm (GSA) and the newly improved GSA (IGSA) for optimization of themixed-integer non-linear electricity generation expansion planning (GEP) problem. The performanceindex of GEP...

In today’s competitive market place, companies seek an efficient structure of supply chain so as to provide customers with highest value and achieve competitive advantage. This requires a broader perspective than just the borders of an individual company during a supply chain. This paper investigates an aggregate production planning problem integrated with distribution issues in a supply chain ...

Most production planning models are deterministic and often assume a linear relation between production volume and production cost. In this paper, we investigate a production planning problem in a steel production process considering the energy consumption cost which is a nonlinear function of the production quantity. Due to the uncertain environment, the production demands are stochastic. Taki...

The classical optimization problem for reducing investment costs and energy loss in radial distribution systems is addressed through a strategy of linear approximations and new variable representation. The linear approximation of the problem is performed in two main aspects: one is by using Support Hipper-planes (SH) allowing the approximation of the loss function in each branch of the distribu...

In this paper, we propose a novel optimization model to plan IEEE 802.11 broadband access networks. From a formal point of view, it is a mixed integer non-linear optimization model that considers both co-channel and inter-channel interference in the same compact formulation. It may serve as a planning tool by itself or to provide a performance bound to validate simpler planning models such as t...

This paper describes ILP-PLAN, a framework for solving AI planning problems represented as integer linear programs. ILP-PLAN extends the planning as satisfiability framework to handle plans with resources, action costs, and complex objective functions. We show that challenging planning problems can be effectively solved using both traditional branchand-bound IP solvers and efficient new integer...