An algorithm is developed to statistically find the best global fit of a nonlinear non-convex cost-function over a D-dimensional space. It is argued that this algorithm permits an annealing schedule for ''temperature'' T decreasing exponentially in annealing-time k, T = T 0 exp(−ck 1/D). The introduction of re-annealing also permits adaptation to changing sensitivities in the multi-dimensional ...

1. Complexities of Problems and Algorithms 2. Introduction to Global Search Methods 3. Contribution of Statistical Physics and Thermodynamics 4. The Simulated Annealing Algorithm 4.1.The Simulated Annealing Algorithm 4.2.Model Calibration and Algorithm Convergence 5. Examples of Problems Solved Thanks to Simulated Annealing 5.1.The Quadratic Assignment Problem 5.2.The Travelling Salesman Proble...

An algorithm of simulated annealing for the job shop scheduling problem is presented. The proposed algorithm restarts with a new value every time the previous algorithm finishes. To begin the process of annealing, the starting point is a randomly generated schedule with the condition that the initial value of the makespan of the schedule does not surpass a previously established upper bound. Th...

In this work, we propose a Hybrid particle swarm optimization-Simulated annealing algorithm and present a comparison with i) Simulated annealing algorithm and ii) Back propagation algorithm for training neural networks. These neural networks were then tested on a classification task. In particle swarm optimization behaviour of a particle is influenced by the experiential knowledge of the partic...

nowadays, one-dimensional cutting stock problem (1d-csp) is used in many industrial processes and re-cently has been considered as one of the most important research topic. in this paper, a metaheuristic algo-rithm based on the simulated annealing (sa) method is represented to minimize the trim loss and also to fo-cus the trim loss on the minimum number of large objects. in this method, the 1d-...

recently, much attention has been given to stochastic demand due to uncertainty in the real -world. in the literature, decision-making models and suppliers' selection do not often consider inventory management as part of shopping problems. on the other hand, the environmental sustainability of a supply chain depends on the shopping strategy of the supply chain members. the supplier selection pl...

An algorithm of simulated annealing for the job shop scheduling problem is presented. The proposed algorithm restarts with a new value every time the previous algorithm finishes. To begin the process of annealing, the starting point is a randomly generated schedule with the condition that the initial value of the makespan of the schedule does not surpass a previously established upper bound. Th...

The main goal of this work is to propose a way for combined use of two nontraditional algorithms by solving topological problems on telecommunications concentrator networks. The algorithms suggested are the Simulated Annealing algorithm and the Genetic Algorithm. The Algorithm of Simulated Annealing unifies the well known local search algorithms. In addition Simulated Annealing allows acceptati...

This paper presents a new simulated annealing algorithm to solve constrained multi-global optimization problems. To compute all global solutions in a sequential manner, we combine the function stretching technique with the adaptive simulated annealing variant. Constraint-handling is carried out through a nondifferentiable penalty function. To benchmark our penalty stretched simulated annealing ...