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...

This article explains how to apply the deterministic annealing (DA) and simulated annealing (SA) methods to fuzzy entropy based fuzzy c-means clustering. By regularizing the fuzzy c-means method with fuzzy entropy, a membership function similar to the Fermi-Dirac distribution function, well known in statistical mechanics, is obtained, and, while optimizing its parameters by SA, the minimum of t...

in this paper, we introduce a methodology for safety stock placement in supply chain. the problem has two objectives: minimization of good's delivery time and inventory cost. because the problem belongs to np-hard category, we develop a proper simulated annealing algorithm (sa) for solve the proposed methodology in large scaled problem. for verify the performance and efficiency of the meth...

This work deals with using a method of artificial intelligence, mainly the generic probabilistic meta-algorithm can be used in such a difficult task which is analyzed and control of dynamical systems. Simulated annealing (SA) is used in this investigation. The adaptive control system was used in simulations with optimization by Simulated Annealing and the results are presented in graphs. Use of...

projects scheduling by the project portfolio selection, something that has its own complexity and its flexibility, can create different composition of the project portfolio. an integer programming model is formulated for the project portfolio selection and scheduling.two heuristic algorithms, genetic algorithm (ga) and simulated annealing (sa), are presented to solve the problem. results of cal...

Simulated annealing (SA) algorithms can be modeled as time-inhomogeneous Markov chains. Much work on the convergence rate of simulated annealing algorithms has been well-studied. In this paper, we propose an adiabatic framework for studying simulated annealing algorithm behavior. Specifically, we focus on the problem of simulated annealing algorithms that start from an initial temperature T0 an...