in recent years, significant research efforts have been devoted to the optimal planning of power systems. substation expansion planning (sep) as a sub-system of power system planning consists of finding the most economical solution with the optimal location and size of future substations and/or feeders to meet the future demand. the large number of design variables, and combination of discrete ...

To deal with severe drought when water supply is insufficient hedging rule, based on hedging rule curve, is proposed. In general, in discrete hedging rules, the rationing factors have changed from a zone to another zone at once. Accordingly, this paper is an attempt to improve the conventional hedging rule to control the changes of rationing factors. In this regard, the simulation model has emp...

In this paper we extend the homogenization method to the optimization of the position of fuel assemblies in a nuclear reactor core. For this type of problem the state equation is a system of diffusion equations for the neutron flux. Homogenization theory allows to relax a truly discrete optimization problem into a continuous and well-posed optimization problem. The latter one is solved by using...

Abstract. We propose an approach to address data uncertainty for discrete optimization and network flow problems that allows controlling the degree of conservatism of the solution, and is computationally tractable both practically and theoretically. In particular, when both the cost coefficients and the data in the constraints of an integer programming problem are subject to uncertainty, we pro...

In the present paper, an approach is proposed for structural topology optimization based on combination of Radial Basis Function (RBF) Level Set Method (LSM) with Isogeometric Analysis (IGA). The corresponding combined algorithm is detailed. First, in this approach, the discrete problem is formulated in Isogeometric Analysis framework. The objective function based on compliance of particular lo...

We study a class of non-convex optimization problems involving sigmoid functions. We show that sigmoid functions impart a combinatorial element to the optimization variables and make the global optimization computationally hard. We formulate versions of the knapsack problem, the generalized assignment problem and the bin-packing problem with sigmoid utilities. We merge approximation algorithms ...

The complexity of any optimisation problem depends critically on the form of the objective function. Valued constraint satisfaction problems are discrete optimisation problems where the function to be minimised is given as a sum of cost functions defined on specified subsets of variables. These cost functions are chosen from some fixed set of available cost functions, known as a valued constrai...

Semi-directed 2-circulant graph is a subgraph of an (undirected) 2-circulant graph in which the links of one type (i.e., short or long) are directed while the other links are undirected. The shortest paths in semi-directed circulant graphs are called the restricted shortest paths in 2-circulant graphs. In this paper we show that the problem of finding the restricted shortest paths is equivalent...

Robust stochastic anisotropy-based H∞-optimization problem for discrete linear time-invariant (LTI) systems with structured parametric uncertainty is considered. It is shown that the problem can be reduced to mixed H2/H∞-like problem. The resulting control problem involves the minimization of anysotropic and H∞ norms of the system. Explicit state-space formulas are also obtained for the optimal...

Finding an optimal schedule of tasks for an application in distributed environment is critical in general. Task assignment is an extremely NP complete problem. This type of problem can be resolved by heuristic algorithms efficiently because the traditional methods such as dynamic programming and the back tracking need more time for solving this NP complete problem. Particle Swarm Optimization (...