this study aims to minimize the total cost of a four-echelon supply chain including suppliers, an assembler, distributers, and retailers. the total cost consists of purchasing raw materials from the suppliers by the assembler, assembling the final product, materials transportation from the suppliers to the assembler, product transportation from the assembler to the distributors, product transpo...

earth dam is a structure as homogeneous or non-homogeneous forms for raising water level or water supply. earth dam consist of different parts that one of the main parts is clay core. choosing an optimal non permeable core which causes reduction of seepage through dam body and also being stable is necessary. the objective of this research is to optimize the geometry of earth dam clay core such ...

We introduce a meta-heuristic to combine simulated annealing with local search methods for CO problems. This new class of Markov chains leads to signiicantly more powerful optimization methods than either simulated annealing or local search. The main idea is to embed deterministic local search techniques into simulated annealing so that the chain explores only local optima. It makes large, glob...

Metaheuristics are general problem solving algorithms which abstract from the actual problem description. Therefore they can be easily applied to many optimization problems. Simulated annealing is a simple and fast metaheuristic with an analogy to metal processing. As metal particles generate a solid and regular structure when cooling slowing simulated annealing seeks a low-energy solution avoi...

Simulated annealing is a well-studied local search metaheuristic used to address discrete and, to a lesser extent, continuous optimization problems. The key feature of simulated annealing is that it provides a mechanism to escape local optima by allowing hill-climbing moves (i.e., moves which worsen the objective function value) in hopes of finding a global optimum. A brief history of simulated...

The efficient search of global optimal solutions is an important contemporary subject. Different optimization methods tackle the search in different ways. The gradient based methods are among the fastest optimization methods but the final optimal solution depends on the starting point. The global search using these methods is carried out by providing many starting points. Other optimization met...

It is difficult to determine the appropriate temperature parameters which control the acceptance probability in Simulated Annealing, which is a typical meta-heuristic method in the optimization methods. In this paper, we propose a new simulated annealing method that determines the maximum temperature adaptively. The proposed method is base on an important temperature where optimum solutions wer...

The paper presents a simulation study of the usefulness of a number of meta-heuristics used as optimisation methods for TSP problems. The five considered approaches are outlined: Genetic Algorithm, Simulated Annealing, Ant Colony System, Tabu Search and Hopfield Neural Network. Using a purpose-developed computer program, efficiency of the meta-heuritics has been studied and compared. Results ob...