We present and summarize the results from 50-, 100-and 200-city TSP benchmarks presented at the 1989 NIPS post-conference workshop using neural network, elastic net, genetic algorithm and simulated annealing approaches. These results are also compared with a state-of-the-art hybrid approach consisting of greedy solution, simulated annealing, and exhaustive search.

A new constraint-driven methodology for the placement of analog IC's is described. Electrical performance speciications are automatically translated into constraints on the layout parasitics. These constraints and the sensitivity information of the circuit are then used to control a Simulated Annealing-based placement algorithm. At each step of the annealing a fast check on performance degradat...

this study aims to deal with a more realistic combined problem of project scheduling and material ordering. the goal is to minimize the total material holding and ordering costs by determining the starting time of activities along with material ordering schedules subject to some constraints. the problem is first mathematically modelled. then a hybrid simulated annealing and genetic algorithm is...

modeling of fermentation processes is so complicated and uncertain; therefore it is necessary to provide a robust and appropriate dynamic optimization method. in order to obtain the maximum amount of yeast (saccharomyces cerevisiae), the bioreactor must be operated under optimal conditions. to determine substrate feeding in a fed-batch bioreactor, a simulated annealing (sa) approach was examine...

This paper presents a multi-objective Particle Swarm Optimization (PSO) algorithm for worker assignment and mixed-model assembly line balancing problem when task times depend on the worker’s skill level. The objectives of this model are minimization of the number of stations (equivalent to the maximization of the weighted line efficiency), minimization of the weighted smoothness index and minim...

In this paper, we demonstrate the ease in which an adaptive simulated annealing algorithm can be designed. Specifically, we use the adaptive annealing schedule known as the modified Lam schedule to apply simulated annealing to the weighted tardiness scheduling problem with sequence-dependent setups. The modified Lam annealing schedule adjusts the temperature to track the theoretical optimal rat...

This paper presents a simulated annealing algorithm that based on multiple search neighborhoods to solve a special kind of timetable problem. The new algorithm also can solve those problems that can be solved by local search algorithm. Various experimental results show that the new algorithm can actually give more satisfactory solutions than general simulated annealing algorithm can do.

Annealing of general iterative stochastic schemes is studied by using Wentzell’s large deviation theory. The convergence of this algorithm is shown under some conditions. The closed form of the critical constant is specified in terms of its potential function of the mean model.