On the convergence of parallel simulated annealing

On the convergence of Parallel Simulated Annealing

Using the Matrix-Tree Theorem and coupling methods the convergence of the Parallel Chain (PC) algorithm to the set of global minima is established for various selection functions. It is illustrated that there may be convergence to a set of non-global minima when selecting one of the best states (Best-Wins strategy). In the latter case the convergence of the homogeneous PC algorithm is proved fo...

On the Convergence Time of Simulated Annealing

Simulated Annealing is a family of randomized algorithms used to solve many combinatorial optimization problems. In practice they have been applied to solve some presumably hard (e.g., NP-complete) problems. The level of performance obtained has been promised [5, 2, 6, 14]. The success of its heuristic technique has motivated analysis of this algorithm from a theoretical point of view. In parti...

Neighborhood Parallel Simulated Annealing

Parallel Simulated Annealing Algorithms

n different nodes of the network. The two algorithms have been applied to the job shop scheduling problem (JSS) and the traveling salesman problem (TSP). Both algorithms showed very good performance in terms of solution time and solution quality. The rest of the paper is organized in the following fashion. Section II describes the simulated annealing technique. Section III presents the cluster ...

Parallel Simulated Annealing for the Delivery Problem

A delivery problem which reduces to an NP-complete set-partitioning problem is considered. Two algorithms of parallel simulated annealing, i.e. the simultaneous independent searches and the simultaneous periodically interacting searches are investigated. The objective is to improve the accuracy of solutions to the problem by applying parallelism. The accuracy of a solution is meant as its proxi...