this study aims to deal with a more realistic combined problem of project scheduling and material ordering. the goal is to minimize the total material holding and ordering costs by determining the starting time of activities along with material ordering schedules subject to some constraints. the problem is first mathematically modelled. then a hybrid simulated annealing and genetic algorithm is...

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 ...

This work deals with using a method of artificial intelligence, mainly the generic probabilistic meta-algorithm can be used in such a difficult task which is analyzed and control of dynamical systems. Simulated annealing (SA) is used in this investigation. The adaptive control system was used in simulations with optimization by Simulated Annealing and the results are presented in graphs. Use of...

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 known to be an efficient method for combinatorial optimization problems. Its usage for realistic problem size, however, has been limited by the long execution time due to its sequential nature. This report presents a practical approach to synchronous simulated annealing for massively parallel distributed-memory multiprocessors. We use an n-ary speculative tree to execute ...

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...

In this paper we discuss the solution of the clustering problem usually solved by the K-means algorithm. The problem is known to have local minimum solutions.A simulated annealing algorithm for the clustering problem. The solution of the clustering problem usually solved by the K-means algorithm.In this paper, we explore the applicability of simulated annealing. Clustering problem is investigat...

In this article, since the year 2003, many heuristic methods have been applied in parallel machine scheduling problem with the simulated annealing method in the literature review. Performing a detailed literature research has revealed that there are numerous heuristic methods applied to parallel machine problems. It is seen that, among these heuristics, simulated annealing yields the best solut...

The accurate synthesis of binary porous media is a difficult problem. Initial applications of simulated annealing in this context with small data sets and simple energy functions have met with limited success. Simulated annealing has been applied to a wide variety of problems in image processing. Particularly in scientific applications such as discussed here, the computational complexity of thi...