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...

It is a long time that the Simulated Annealing (SA) procedure has been introduced as a model-free optimization for solving NP-hard problems. Improvements from the standard SA in the recent decade mostly concentrate on combining its original algorithm with some heuristic methods. These modifications are rarely happened to the initial condition selection methods from which the annealing schedules...

Annealing algorithms have been employed extensively in the past decade to solve myriads of optimization problems. Several intractable problems such as the traveling salesperson problem, graph partitioning, circuit layout, etc. have been solved to get satisfactory results. In this article we survey convergence results known for annealing algorithms. In particular we deal with Simulated Annealing...

optimization of cutting conditions is a non-linear optimization with constraint and it is very important to the increase of productivity and the reduction of costs. in recent years, several evolutionary and meta-heuristic optimization algorithms were introduced. the cuckoo optimization algorithm (coa) is one of several recent and powerful meta-heuristics which is inspired by the cuckoos and the...

This report proposes a double simulated annealing (DSA) for functional magnetic resonance image (fMRI) analysis. The first simulated annealing (SA) is used to disconnect the brain from the skull. The second SA is applied to locate the activation area of the fMRIs. The performance evaluation of this approach includes receiver-operating characteristic (ROC) analysis, similarity analysis, and comp...

This paper introduces the main ideas of the nested partitions (NP) method, analyses its efficiency theoretically and proposes the way to improve the optimization efficiency of the algorithm. Then the paper introduces the simulated annealing (SA) algorithm and incorporates the ideas of SA into two of the arithmetic operators of NP algorithm to form the combined NP/SA algorithm. Moreover, the pap...