Article history: Received: 13.2.2015. Received in revised form: 24.3.2015. Accepted: 27.3.2015. In structural design optimization method, numerical techniques are increasingly used. In typical structural optimization problems there may be many locally minimum configurations. For that reason, the application of a global method, which may escape from the locally minimum points, remains essential....

In this paper we apply stochastic methods (Gibbs sampling and simulated annealing) and deterministic (mean eld) approximations to the problem of detecting and interpolating`dirt and sparkle' or`blotches' in archived motion pictures.

The 0-1 Multidimensional Knapsack Problem (MKP) is a widely-studied problem in combinatorial optimization domaine which has been proven as NP-hard. Various approximate heuristics have been developed and applied effectively to this problem, such as local search and evolutionary methods. This paper proposes the Stochastic Local Search-Simulated Annealing (SLSA) approach that combines the stochast...

Much of the research in facility layout has focused on static layouts where the material handling flow is assumed to be constant during the planning horizon. But in today’s market-based, dynamic environment, layout rearrangement may be required during the planning horizon to maintain layout effectiveness. A few algorithms have been proposed to solve this problem. They include dynamic programmin...

Simulated annealing is a powerful stochastic search method, but it still has the disadvantage of blind search. Tabu search (TS) which can prevent cycling and enhance diversi/cation, is an adaptive strategy based on tabu list. By reasonably combining simulated annealing with TS, an e#ective hybrid algorithm for the problem of packing circles into a larger containing circle is presented. Based on...

The integration of an approximate model and a clonal selection algorithm (CSA) is considered as one of the most effective ways to solve complex optimization design problems in engineering. In this study, first, a process for developing an approximate model and the principles of clonal selection algorithms is presented. Second, a variotherm temperature injection mold was used to produce a large ...

This paper presents an algorithm for solving a multi-floor facility layout problem. The most apparent difference and also the potential difficulty in a multi-floor facility layout problem, compared to a single floor facility layout problem, are the problems regarding the placement of the vertical transportation equipments (elevators), which are to be used for vertical transportation occuring wi...

the network design problem (ndp) is one of the important problems in combinatorial optimization. among the network design problems, the multicommodity capacitated network design (mcnd) problem has numerous applications in transportation, logistics, telecommunication, and production systems. the mcnd problems with splittable flow variables are np-hard, which means they require exponential time t...

Various problems of combinatorial optimization and permutation can be solved with neural network optimization. The problem of estimating the software reliability can be solved with the optimization of failed components to its minimum value. Various solutions of the problem of estimating the software reliability have been given. These solutions are exact and heuristic, but all the exact approach...

It is a long time that the Simulated Annealing (SA) procedure has been introduced as a model-free optimization for solving NP-hard problems. Improvements from the standard SA in the recent decade mostly concentrate on combining its original algorithm with some heuristic methods. These modifications are rarely happened to the initial condition selection methods from which the annealing schedules...