We describe a comparison between Simulated Annealing (SA), Dispatch Rules (DR), and a Coevolutionary Distributed Genetic Algorithm (DGA) solving a random sample of integrated planning and scheduling (IPS) problems. We found that for a wide range of optimization criteria the DGA consistently outperformed SA and DR. The DGA finds 8-9 unique high quality solutions per run, whereas the other techni...

Simulated annealing (SA) was inspired from annealing in metallurgy, a technique involving heating and controlled cooling of a material to increase the size of its crystals and reduce their defects, both are attributes of the material that depend on its thermodynamic free energy. In this Paper, firstly we will study SA in details on its initial feasible solution choosing, initial temperature sel...

The performance of simulated annealing (SA) algorithms mainly depends on how to determine the SA-related parameters. Schemes as well as corresponding parameter values for defining the schemes should be appropriately determined. In this paper, we propose an advanced robust design method and apply it to the mixed-model sequencing problem which is known to be NP-hard. The proposed method considers...

The objective of the Power System Stabilizer (PSS) is added to excitation system to enhance the damping during low frequency oscillations. This paper presents a comparison study of Simulated Annealing and fast output sampling based power system stabilizer (PSS) for stability enhancement. Conventional Power system stabilizers (CPSSs) are designed with the phase compensation technique in the freq...

We experimentally analyze the general applicability of genetic algorithms (GA) and simulated annealing algorithms (SA) for mapping data to multicomputers. The results show that the GA and SA are insensitive to user parameters in wide ranges, completely fault tolerant, and unbiased towards particular multicomputer topologies. These properties of flexibility and general applicability, which are l...

this paper addresses the vehicle routing problem with delivery time cost. this problem aims to find a set of routes of minimal total costs including the travelling cost and delivery time cost, starting and ending at the depot, in such a way that each customer is visited by one vehicle given the capacity of the vehicle to satisfy a specific demand. in this research, a hybrid metaheuristic approa...

In this paper a simulated annealing (SA) algorithm is presented for the 0/1 multidimensional knapsack problem. Problem-specific knowledge is incorporated in the algorithm description and evaluation of parameters in order to look into the performance of finite-time implementations of SA. Computational results show that SA performs much better than a genetic algorithm in terms of solution time, w...

In this paper, the author proposes the application of a genetic algorithm and simulated annealing to solve the network planning problem. Compared with other optimisation methods, genetic algorithm and simulated annealing are suitable for traversing large search spaces since they can do this relatively rapidly and because the use of mutation diverts the method away from local minima, which will ...

In this paper, we design genetic algorithm and simulated annealing algorithm and their parallel versions to solve the Closest String problem. Our implementation and experiments show usefulness of the parallel GA and SA algorithms.

Bus network design is an important problem in public transportation. A main step to this design is determining the number of required terminals and their locations. This is a special type of facility location problem, which is a time-consuming, large scale, combinatorial problem. In a previous attempt by the authors, this problem had been solved by GAMS, based on a branch and bound algorithm.&...