We present an in-depth study of the simulated annealing approach to the scheduling of serial multiproduct batch processes under the assumption of a permutation schedule. Four versions of the simulated annealing algorithm are studied based on two move acceptance criteria, the Metropolis algorithm and the Glauber algorithm, and two annealing schedules, the exponential schedule and the Aarts and v...

Simulatedannealing (SA) Wutiques have shown great potential to generate geologically realistic permeability fields by combining data from many sources, such as well logs, cores, and tracer tests. However, the application of SA in reservoir description and simulation is limited owing to its prohibitively large computational time requirement, even on modern MqXWornputem. This paper introduces an ...

In this paper, we propose a new hybrid scheme of parallel tempering and simulated annealing (hybrid PT/SA). Within the hybrid PT/SA scheme, a composite system with multiple conformations is evolving in parallel on a temperature ladder with various transition step sizes. The simulated annealing (SA) process uses a cooling scheme to decrease the temperature values in the temperature ladder to the...

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...

In this paper, a Temperature Parallel Simulated Annealing with Adaptive Neighborhood (TPSA/AN) for continuous optimization problems is introduced. TPSA/AN is based on the temperature parallel simulated annealing (TPSA), which is suitable for parallel processing, and the SA that Corana developed for continuous optimization problems. The moves in TPSA/AN are adjusted to have equal acceptance rate...

Assigning cells to switches in cellular mobile networks is an NP-hard problem which, for realsize mobile networks, could not be solved by using exact methods. In this context, heuristic approaches like genetic algorithms, tabu search and simulated annealing can be used. This paper proposes a comparative study of three heuristics—tabu search, simulated annealing and Parallel Genetic Algorithms w...

Multidisciplinary Design Optimization (MDO) is the most active fields in the current complex engineering system design. Forcing to the defects of traditional Collaborative Optimization, such as unable to convergence or falling into local optimum, we propose a Collaborate Optimization based on Simulated Annealing and Artificial Neural Networks, (SA-ANN-CO). The SA-ANN-CO algorithm inherit the pa...

Appropriate scheduling and sequencing of tasks on machines is one of the basic and significant problems that a shop or a factory manager encounters; this is why in recent decades extensive studies have been done on scheduling issues. One type of scheduling problems is just-in-time (JIT) scheduling and in this area, motivated by JIT manufacturing, this study investigates a mathematical model for...

Global optimization involves the difficult task of the identification of global extremities of mathematical functions. Such problems are often encountered in practice in various fields, e.g., molecular biology, physics, industrial chemistry. In this work, we develop five different parallel Simulated Annealing (SA) algorithms and compare them on an extensive test bed used previously for the asse...

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...