− In this paper, we propose a Simulated Annealing PolyClonal Selection Algorithm (SAPCSA) for Traveling Salesman Problems (TSP). By introducing a simulated annealing (SA) strategy to the PolyClonal Selection Algorithm (PCSA), the SAPCSA integrate the characteristics of both SA and PCSA. Numerous instances have been simulated to verify the proposed algorithm.

This research presents a new application of the cloud theory-based simulated annealing algorithm to solve mixed model assembly line sequencing problems where line stoppage cost is expected to be optimized. This objective is highly significant in mixed model assembly line sequencing problems based on just-in-time production system. Moreover, this type of problem is NP-hard and solving this probl...

This paper studies quantum annealing (QA) for clustering, which can be seen as an extension of simulated annealing (SA). We derive a QA algorithm for clustering and propose an annealing schedule, which is crucial in practice. Experiments show the proposed QA algorithm finds better clustering assignments than SA. Furthermore, QA is as easy as SA to implement.

We introduce four new general optimization algorithms based on the ‘demon’ algorithm from statistical physics and the simulated annealing (SA) optimization method. These algorithms reduce the computation time per trial without significant effect on the quality of solutions found. Any SA annealing schedule or move generation function can be used. The algorithms are tested on traveling salesman p...

in this paper, we investigate a decision support system (dss) for the resolution of real-life vehicle routing and scheduling problem (vrsp). scheduling the deliveries from a regional distribution centre (rdc) to large stores of a major fmcg retailer includes every possible vehicle routing complexity. usual constraints that are seen are: size of the vehicle and the length of the driving day, loa...

Simulated annealing (SA) presents an optimization technique with several striking positive and negative features. Perhaps its most salient feature, statistically promising to deliver an optimal solution, in current practice is often spurned to use instead modified faster algorithms, “simulated quenching” (SQ). Using the author’s Adaptive Simulated Annealing (ASA) code, some examples are given w...

The Methodology to Parallelize Simulated Annealing (MPSA) leads to massive parallelization by executing each temperature cycle of the Simulated Annealing (SA) algorithm in parallel. The initial solution for each internal cycle is set through a Monte Carlo random sampling to adjust the Boltzmann distribution at the cycle beginning. MPSA uses an asynchronous communication scheme and any implement...

Combinatorial optimization problems arise in different fields of science and engineering. There exist some general techniques coping with these problems such as simulated annealing (SA). In spite of SA success, it usually requires costly experimental studies in fine tuning the most suitable annealing schedule. In this Letter, the classical integrated circuit placement problem is faced by Thermo...