The interval linear programming (IvLP) 1 is a method for decision making under uncertainty. A weak feasible solution to IvLP is called weakly optimal if it is optimal for some scenario of the IvLP. One of the basic and difficult tasks in IvLP is to check whether a given point is weak optimal. In this paper, we investigate linear programming problems with interval right-hand side. Some necessary...

This paper introduces a new hybrid evolutionary algorithm (EA) for continuous global optimization problems, called estimation of distribution algorithm with local search (EDA/L). Like other EAs, EDA/L maintains and improves a population of solutions in the feasible region. Initial candidate solutions are generated by uniform design, these solutions evenly scatter over the feasible solution regi...

‎a full nesterov-todd (nt) step infeasible interior-point algorithm‎ ‎is proposed for solving monotone linear complementarity problems‎ ‎over symmetric cones by using euclidean jordan algebra‎. ‎two types of‎ ‎full nt-steps are used‎, ‎feasibility steps and centering steps‎. ‎the‎ ‎algorithm starts from strictly feasible iterates of a perturbed‎ ‎problem‎, ‎and, using the central path and feasi...

introduction: the appropriate-use optimization of the limited spaces of the iranian hospitals is believed to be a crucial step towards promoting the efficiency of these healthcare centers. the issue determining the optimization patterns of the layout of units has led to a lot of efforts by researchers as it increases the efficiency of the hospitals through patients’ improvement, changing the lo...

We present here a simple probabilistic approach for determining an optimal progressive censoring scheme by defining probability structure on the set of feasible solutions. Given initial solution, new updated solution is computed within structure. This will be especially useful when cardinality solutions large. The validation proposed demonstrated comparing so determined with one obtained exhaus...

A reassignment heuristic, originally designed to produce good solutions to an optimisation problem in rostering, is generalised so that it can, at least in theory, nd a feasible solution to any constraint satisfaction problem (CSP), if one exists. The heuristic requires an initial solution which is consistent but incomplete, in that some variables may be unassigned. Each unassigned variable is ...

GRASP (Greedy Randomized Adaptive Search Procedures) is a multistart metaheuristic for producing good-quality solutions of combinatorial optimization problems. Each GRASP iteration is usually made up of a construction phase, where a feasible solution is constructed, and a local search phase which starts at the constructed solution and applies iterative improvement until a locally optimal soluti...

An ultimate aim of this present paper is to solve application problem such as robot arm and initial value problems by applying Runge-Kutta fifth order five stage numerical techniques. The calculated output for robot arm coincides with exact solution which is found to be better, suitable and feasible for solving real time problems.

Adsorption of Chromium ions (VI) and (III) in aqueous solution was investigated using activated carbon prepared from olive wastes, by one step physical activation with steam. After adsorbent material characterization using adsorption capacity of methylene blue, iodine and phenol, BET surface area, Fourier Transform InfraRed (FT-IR) spectroscopy, pHpzc, surface functions based on the Boehm m...

Inverse optimization perturbs objective function to make an initial feasible solution optimal with respect to perturbed objective function while minimizing cost of perturbation. We extend inverse optimization to two-stage stochastic linear programs. Since the resulting model grows with number of scenarios, we present two decomposition approaches for solving these problems.