In this paper, we propose a population-based optimization algorithm, Sequential Monte Carlo Simulated Annealing (SMC-SA), for continuous global optimization. SMC-SA incorporates the sequential Monte Carlo method to track the converging sequence of Boltzmann distributions in simulated annealing. We prove an upper bound on the difference between the empirical distribution yielded by SMC-SA and th...

Single row layout is one of the most usually used layout patterns in industries, particularly in flexible manufacturing systems. Here actual sequencing of machine and arrangement of parts, no doubt, have a great influence on the throughput of the flexible manufacturing system i.e., (F.M.S). This paper discusses the single row layout design in flexible manufacturing system (F.M.S). This paper fu...

this paper aims to investigate the integrated production/distribution and inventory planning for perishable products with fixed life time in the constant condition of storage throughout a two-echelon supply chain by integrating producers and distributors. this problem arises from real environment in which multi-plant with multi-function lines produce multi-perishable products with fixed life ti...

In this paper, three simulated annealing based algorithms that exploit auxiliary knowledge in different ways are devised and employed to handle a manufacturing process planning problem for reconfigurable manufacturing. These algorithms are configured based on a generic combination of the simulated annealing technique with; (a) heuristic knowledge, and (b) metaknowledge. Capabilities of the impl...

In this paper, we focus on solving global optimization problems using only the values of the objective function. In particular we explore the Simulated Annealing method, and find improvements using techniques in Derivative Free Optimization methods. The first part of the paper examines the well known Simulated Annealing algorithm. We discuss important theoretical results, and we then demonstrat...

In this paper, a simulated-annealing-based method called Filter Simulated Annealing (FSA) method is proposed to deal with the constrained global optimization problem. The considered problem is reformulated so as to take the form of optimizing two functions, the objective function and the constraint violation function. Then, the FSA method is applied to solve the reformulated problem. The FSA me...

The aim of this paper is to examine two new simulated annealing approaches for Uncapacitated Facility Location (UFL) problems with some useful comparisons with the latest genetic algorithm approach (Jaramillo et al, 2002) to the problem. As it is mentioned in various publications, the simulated annealing approach may be very successful in terms of quality of the solution but not so impressive w...

With the formation of the competitive electricity markets in the world, optimization of bidding strategies has become one of the main discussions in studies related to market designing. Market design is challenged by multiple objectives that need to be satisfied. The solution of those multi-objective problems is searched often over the combined strategy space, and thus requires the simultaneous...

An MCM's increased throughput and dense circuitry can easily result in failure if the board contains \hot spots". Therefore, an accurate thermal model of an MCM was needed in the development of a new placement algorithm designed to consider both total net length and heat constraints. This algorithm uses a combination of simulated evolution and simulated annealing in an iterative approach. The t...

This paper proposes a multi-objective memetic algorithm based on NSGA-II and Simulated Annealing (SA), NSGA-II-SA, for calibration of microscopic vehicular traffic flow simulation models. The NSGA-II algorithm performs a scan in the search space and obtains the Pareto front which is optimized locally with SA. The best solution of the obtained front is selected. Two CORSIM models were calibrated...