Simulated annealing is a popular local search meta-heuristic used to address discrete and, to a lesser extent, continuous optimization problems. The key feature of simulated annealing is that it provides a means to escape local optima by allowing hill-climbing moves (i.e., moves which worsen the objective function value) in hopes of finding a global optimum. A brief history of simulated anneali...

In this paper, we propose sequential Monte Carlo simulated annealing (SMC-SA), a populationbased simulated annealing algorithm, for continuous global optimization. SMC-SA incorporates the sequential Monte Carlo method to track the converging sequence of Boltzmann distributions in simulated annealing, such that the empirical distribution will converge weakly to the uniform distribution on the se...

We proposed a passenger control strategy and train operation plan collaborative optimization (PCS&TOP) model to schedule the that improves efficiency of passengers’ travel reduces cost for rail transit network. The is an integer non linear programming aims minimize entrance platform waiting time passengers trains. timetable variable formation are integrated optimized, turnaround rolling sto...

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 stochastic multi-depot multi-objective vehicle routing problem (vrp) is studied. based on observations in real-world problems, we develop an aspect of the problem, such as stochastic availability of routes. to solve the problem in this situation, a two-objective mathematical model is developed, in which the related objective functions are: (1) minimizing transportation costs an...