This paper describes two parallel simulated annealing algorithms for the job shop scheduling problem with the sum of job completion times criterion. Some properties of the problem associated with the block theory have been presented and discussed. These properties allow us to introduce the effective neighborhood based on the adjacent swap type moves. In this paper, an original method for parall...

A covering array (CA) is a combinatorial structure specified as a matrix of N rows and k columns over an alphabet on v symbols such that for each set of t columns every t-tuple of symbols is covered at least once. Given the values of t, k, and v, the optimal covering array construction problem (CAC) consists in constructing a CA(N ; t, k, v) with the minimum possible value of N . There are seve...

The co-operation of parallel simulated annealing processes to solve the vehicle routing problem with time windows (VRPTW) is considered. The objective is to investigate how the number of parallel processes and the frequency of processes co-operation influence the accuracy of solutions to the VRPTW. The accuracy of solutions is measured by their proximity to the best known solution.

In this paper we address a multi-objective scheduling problem for unrelated parallel machines. In unrelated parallel systems, the processing cost/time of a given job on different machines may vary. The objective of scheduling is to simultaneously determine the job-machine assignment and job sequencing on each machine. In such a way the total cost of the schedule is minimized. The cost function ...

In this paper we present our practical experience with the design and implementation of a suite of parallel algorithms called PARODS, for chromosome reconstruction via ordering of DNA sequences. PARODS contains parallel algorithms based on an earlier serial algorithm ODS which is a physical mapping algorithm based on simulated annealing. The parallel simulated annealing (PSA) algorithms for phy...

This research presents a Simulated Annealing based technique to address the assembly line balancing problem for multiple objective problems when paralleling of workstations is permitted. The Simulated Annealing methodology is used for 23 line balancing strategies across seven problems. The resulting performance of each solution was studied through a simulation experiment. Many of the problems c...

Solving the hard Satisfiability Problem is time consuming even for modest-sized problem instances. Solving the Random L-SAT Problem is especially difficult due to the ratio of clauses to variables. This report presents a practical approach to solving the Random L-SAT Problem on a large-scale distributed-memory multiprocessor. In particular, we use a parallel synchronous simulated annealing proc...

In this paper simulated annealing and genetic algorithms are applied to the graph partitioning problem. These techniques mimic processes in statistical mechanics and biology, respectively, and are the most popular meta-heuristics or general-purpose optimization strategies. A hybrid algorithm for circuit partitioning, which uses tabu search to improve the simulated annealing meta-heuristics, is ...

Two well known stochastic optimization algorithms, simulated annealing and genetic algorithm are compared when using a sample to minimize an objective function which is the expectation of a random variable. Since they lead to minimum depending on the sample, a weighted version of simulated annealing is proposed in order to reduce this kind of overt bias. The algorithms are implemented on an opt...