Simulated annealing has proven to be a good technique for solving hard combina-torial optimization problems. Some attempts at speeding up annealing algorithms have been based on shared memory multiprocessor systems. Also parallelizations for certain problems on distributed memory multiprocessor systems are known. In this paper, we present a problem independent general purpose parallel implement...

Simulated annealing has proven to be a good technique for solving hard combinatorial optimization problems. Some attempts at speeding up annealing algorithms have been based on shared memory multiprocessor systems. Also parallelizations for certain problems on distributed memory multiprocessor systems are known. In this paper, we present a problem independent general purpose parallel implementa...

In this paper, a Job shop scheduling problem with a parallel assembly stage and Lot Streaming (LS) is considered for the first time in both machining and assembly stages. Lot Streaming technique is a process of splitting jobs into smaller sub-jobs such that successive operations can be overlapped. Hence, to solve job shop scheduling problem with a parallel assembly stage and lot streaming, deci...

We compare the two well-known global optimization methods, simulated annealing and genetic optimization, to a local gradient-based optimization technique. We rate the applicability of each method in terms of the minimal achievable target value for a given number of simulation runs in an inverse modeling application. The gradient-based optimizer used in the experiment is based on the Levenberg-M...

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...

this paper studies the hybrid flow shop scheduling where the optimization criterion is the minimization of total tardiness. first, the problem is formulated as a mixed integer linear programming model. then, to solve large problem sizes, an artificial immune algorithm hybridized with a simple local search in form of simulated annealing is proposed. two experiments are carried out to evaluate th...

one main group of a transportation network is a discrete hub covering problem that seeks to minimize the total transportation cost. this paper presents a multi-product and multi-mode hub covering model, in which the transportation time depends on travelling mode between each pair of hubs. indeed, the nature of products is considered different and hub capacity constraint is also applied. due to ...

This paper analyses alternatives for the parallelization of the Simulated Annealing algorithm when applied to the placement of modules in a VLSI circuit considering the use of PVM on an Ethernet cluster of workstations. It is shown that different parallelization approaches have to be used for high and low temperature values of the annealing process. The algorithm used for low temperatures is an...

A personification heuristic Genetic Algorithm is established for the placement of digital microfluidics-based biochips, in which, the personification heuristic algorithm is used to control the packing process, while the genetic algorithm is designed to be used in multi-objective placement results optimizing. As an example, the process of microfluidic module physical placement in multiplexed in-...

Motivated by the success of genetic algorithms and simulated annealing in hard optimization problems, the authors propose a new Markov chain Monte Carlo (MCMC) algorithm called an evolutionary Monte Carlo algorithm. This algorithm has incorporated several attractive features of genetic algorithms and simulated annealing into the framework of MCMC. It works by simulating a population of Markov c...