Papers by Keyword: Simulated Annealing (SA)

Abstract: Tardiness scheduling problems in the lean production has received extensive attention recently, and in most tardiness scheduling problems job due dates are regarded as invariable and known in advance. The study deals with fuzzy tardiness scheduling for parallel machines with fuzzy job due dates, where the objective is to minimize the average penalty cost of jobs tardiness. To describe the tardy degree of job clearly, a novel tardiness measure index is introduced based on the possibility and necessity measures in the study. And further, the mixed integer programming scheduling model of parallel machines is constructed for jobs tardiness. Since this problem is NP-hard, an improved simulated annealing is proposed and designed to solve the model. Finally, a numerical experiment is presented to illustrate the feasibility and effectiveness of the proposed method.

Abstract: Message ferry is a controllable mobile node equipped with long distance communication antennas and rechargeable energy, to collect data in sparse wireless networks and delivery it to the base station. The Energy-Constrained Ferry Route Design (ECFRD) Problem aims to schedule the ferry route when the energy of the ferry is not sufficient to access all the nodes in the network in one tour without charging, so as to minimize the total route length of the ferry. In this paper, we propose a simulated annealing based algorithm to solve the ECFRD problem. The experimental results show that the algorithm proposed in this paper can greatly reduce the total route length of the ferry, comparing the classic nearest neighbor algorithm.

Abstract: In order to resolve the vehicle routing problem with soft time window, a kind of Partheno-genetic Algorithms combined with Simulated Annealing was proposed in the paper, inverse operator and 2-change operator were presented.Centre point was replaced by the dummy natural number, then it is easy to made use of the available methods using by TSP. A selection method with tournament of three copies can keep the diversity of population. The simulation results show that new algorithm can effectively resole VRPTW, and get better results than common GA, new algorithms searching efficiency and convergence probability are effectively enhanced.

Abstract: This paper studies the problem of allocating buffers in stochastic production flow lines with product travel time. We build a model that decomposes the production line into the S-B-S (Station-Buffer-Station) subsystems, and use queueing theory to aggregate the subsystems. Experiments are designed for both balanced and unbalanced production lines, and with the computational results, some general rules for the buffer allocation problem are proposed.

Abstract: An improved large envelope nonlinear flight control method using active disturbances rejection control (ADRC) method and wavelet neural network is approved in this paper. Wavelet neural network is used to realize the inversion of the 6-DOF nonlinear airplane model. The wavelet neural network is optimized using simulated annealing particle swarm optimization algorithm to improve the approach precision. In order to improve the robustness and control performance in all disturbances, ADRC is used to realize the high precision flight control. The simulation results show that the large envelope flight controller has excellent control performance.

Abstract: Hypergraph partitioning is an increasingly important and widely studied research topic in parallel scientific computing. In this paper, we present a multiway hypergraph partitioning algorithm, mixed simulated annealing algorithm for global optimization and tabu search algorithm for local optimization. Experiments on the benchmark suite of several unstructured meshes show that, for 2-, 4-, 8-, 16-and 32-way partitioning, the quality of partition produced by our algorithm are on the average 6% and the maximum 17% better than those produced by partitioning software hMETIS in term of the cutsize metric.

Abstract: Multilevel hypergraph partitioning is a significant and extensively researched problem in combinatorial optimization. In this paper, we present a multilevel hypergraph partitioning algorithm based on simulated annealing approach for global optimization. Experiments on the benchmark suite of several unstructured meshes show that, for 2-, 4-, 8-, 16-and 32-way partitioning, although more running time was demanded, the quality of partition produced by our algorithm are on the average 14% and the maximum 22% better than those produced by partitioning software hMETIS in term of the SOED metric.

Abstract: In this paper we compare the performance of metaheuristic methods, namely simulated annealing and Tabu Search, against simple hill climbing heuristic on a supply chain optimization problem. The benchmark problem we consider is the retailer replenishment optimization problem for a retailer selling multiple products. Computation and simulation results demonstrate that simulated annealing and Tabu search improve solution quality. However, the performance improvement is less in simulations with random noise. Lastly, simulated annealing appears to be more robust than Tabu search, and the results justify its extra implementation effort and computation time when compared against hill climbing.

Abstract: tem-item collaborative filtering was widely used in item recommender system because of good recommend effects. However when facing a large amount of items, there would be performance reduction, because of building a very large item comparison dataset in order to find the similar item. K-means cluster had a very good effect in classification and a good performance even though the dataset being processed is very large. But the cold start was a problem to k-means and we must do some extra work to use it in item recommendation. By using the simulated annealing theory to combine the two methods to fixed the problems of the two methods mentioned above and take use of their advantages for better recommendation effect and performance. The experimental results show that, using simulated annealing to combine the clustering and collaborative filtering in item recommendation system can get more stable recommendation results of better quality.

Abstract: The glass epoxy polymer composites are broadly used in various engineering fields because of outstanding properties. Even if, these composites are produced as near net shapes, the machining has to be carried out in the last stage of manufacture. Drilling is used to install the fasteners for assembly of laminates, but drilling of composites is somewhat complex task owing to exceedingly abrasive nature of reinforcement. Hence the choice of optimal process parameters is essential for successful machining performance. This paper illustrates the application of simulated annealing (SA) approach for simultaneous minimization of various machinability aspects such as thrust force, hole surface roughness and specific cutting coefficient during drilling of glass epoxy polymer composites. The experiments were performed as per full factorial design (FFD) for glass epoxy composites (without filler) and silicon carbide (SiC) filled glass epoxy composites materials. The mathematical models of proposed machinability characteristics were constructed using response surface methodology (RSM) with spindle speed and feed as controllable factors. The experimental investigation indicates that the SiC filled glass epoxy composite provides better machinability compared to glass epoxy composite without the addition of filler. The proposed machinability models were then utilized with SA to select the optimal parameters such as spindle speed and feed, which results in minimal thrust force, hole surface roughness and specific cutting coefficient.