A Hybrid Hypergraph Partitioning Algorithm for Scientific Computing

2013 ◽  
Vol 753-755 ◽  
pp. 2900-2903
Author(s):  
Yao Yuan Zeng ◽  
Wen Tao Zhao ◽  
Zheng Hua Wang
Keyword(s):  
Scientific Computing ◽  
Simulated Annealing Algorithm ◽  
Search Algorithm ◽  
Research Topic ◽  
Hypergraph Partitioning ◽  
Benchmark Suite ◽  
Annealing Algorithm ◽  
Partitioning Algorithm ◽  
Better Than

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.

A Multilevel Hypergraph Partitioning Algorithm Based on Simulated Annealing

2013 ◽  
Vol 753-755 ◽  
pp. 2908-2911
Author(s):  
Yao Yuan Zeng ◽  
Wen Tao Zhao ◽  
Zheng Hua Wang
Keyword(s):  
Global Optimization ◽  
Simulated Annealing ◽  
Combinatorial Optimization ◽  
Unstructured Meshes ◽  
Running Time ◽  
Hypergraph Partitioning ◽  
Benchmark Suite ◽  
Partitioning Algorithm ◽  
Better Than

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.

scholarly journals Multilevel k-way Hypergraph Partitioning

VLSI Design ◽  
2000 ◽  
Vol 11 (3) ◽  
pp. 285-300 ◽  
Author(s):  
George Karypis ◽  
Vipin Kumar
Keyword(s):  
State Of The Art ◽  
Hypergraph Partitioning ◽  
Benchmark Suite ◽  
Partitioning Algorithm ◽  
Better Than

In this paper, we present a new multilevel k-way hypergraph partitioning algorithm that substantially outperforms the existing state-of-the-art K-PM/LR algorithm for multi-way partitioning, both for optimizing local as well as global objectives. Experiments on the ISPD98 benchmark suite show that the partitionings produced by our scheme are on the average 15% to 23% better than those produced by the K-PM/LR algorithm, both in terms of the hyperedge cut as well as the (K – 1) metric. Furthermore, our algorithm is significantly faster, requiring 4 to 5 times less time than that required by K-PM/LR.

scholarly journals Evacuation Network Optimization Model with Lane-Based Reversal and Routing

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Xing Zhao ◽  
Zhao-yan Feng ◽  
Yan Li ◽  
Antoine Bernard
Keyword(s):  
Emergency Response ◽  
Network Optimization ◽  
Optimization Model ◽  
Simulated Annealing Algorithm ◽  
Search Algorithm ◽  
Single Arc ◽  
Annealing Algorithm ◽  
Upper Level ◽  
Reversal Design ◽  
Lane Based

Sometimes, the evacuation measure may seem to be the best choice as an emergency response. To enable an efficiency evacuation, a network optimization model which integrates lane-based reversal design and routing with intersection crossing conflict elimination for evacuation is constructed. The proposed bilevel model minimizes the total evacuation time to leave the evacuation zone. A tabu search algorithm is applied to find an optimal lane reversal plan in the upper-level. The lower-level utilizes a simulated annealing algorithm to get two types of “a single arc for an intersection approach” and “multiple arcs for an intersection approach” lane-based route plans with intersection crossing conflict elimination. An experiment of a nine-intersection evacuation zone illustrates the validity of the model and the algorithm. A field case with network topology of Jianye District around the Nanjing Olympics Sports Center is studied to show the applicability of this algorithm.

scholarly journals Simulated Annealing with Previous Solutions Applied to DNA Sequence Alignment

2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Ernesto Liñán-García ◽  
Lorena Marcela Gallegos-Araiza
Keyword(s):  
Simulated Annealing ◽  
Sequence Alignment ◽  
Simulated Annealing Algorithm ◽  
Multiple Sequence ◽  
Heating And Cooling ◽  
Dna Sequence Alignment ◽  
Alignment Problem ◽  
Simple Change ◽  
Annealing Algorithm

A new algorithm for solving sequence alignment problem is proposed, which is named SAPS (Simulated Annealing with Previous Solutions). This algorithm is based on the classical Simulated Annealing (SA). SAPS is implemented in order to obtain results of pair and multiple sequence alignment. SA is a simulation of heating and cooling of a metal to solve an optimization problem. In order to select randomly a current solution, SAPS algorithm chooses a solution from solutions that have been previously generated within the Metropolis Cycle. This simple change has led to increase the quality of the solution to the problem of aligning genomic sequences with respect to the classical Simulated Annealing algorithm. The parameters of SAPS, for certain instances, are tuned by an analytical method, and some parameters have experimentally been tuned. SAPS has generated high-quality results in comparison with the classical SA. The instances used are specific genes of the AIDS virus.

scholarly journals Scheduling Optimization of Sugarcane Harvest Using Simulated Annealing Algorithm

2018 ◽  
Vol 5 (2) ◽  
pp. 138-147
Author(s):  
Eka Nur Afifah ◽  
Alamsyah Alamsyah ◽  
Endang Sugiharti
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Planning Process ◽  
Search Algorithm ◽  
Raw Material ◽  
Local Search Algorithm ◽  
Harvest Scheduling ◽  
Actual Result ◽  
Material Supply ◽  
Annealing Algorithm

Scheduling is one of the important part in production planning process. One of the factor that influence the smooth production process is raw material supply. Sugarcane supply as the main raw material in the making of sugar is the most important componen. The algorithm that used in this study was Simulated Annealing (SA) algorithm. SA apability to accept the bad or no better solution within certain time distinguist it from another local search algorithm. Aim of this study was to implement the SA algorithm in scheduling the sugarcane harvest process so that the amount of sugarcane harvest not so differ from mill capacity of the factory. Data used in this study were 60 data from sugarcane farms that ready to cut and mill capacity 1660 tons. Sugarcane harvest process in 19 days producing 33043,76 tons used SA algorithm and 27089,47 tons from factory actual result. Based on few experiments, obtained sugarcane harvest average by SA algorithm was 1651,63 tons per day and factory actual result was 1354,47 tons. Result of harvest scheduling used SA algorithm showed not so differ average from mill capacity of factory. Truck uses scheduling by SA algorithm showed average 119 trucks per day while from factory actual result was 156 trucks. With the same harvest time, SA algorithm result was greater  and the amount of used truck less than actual result of factory. Thus, can be concluded SA algorithm can make the scheduling of sugarcane harvest become more optimall compared to other methods applied by the factory nowdays.

scholarly journals Fault Localization Based on Hybrid Genetic Simulated Annealing Algorithm

2021 ◽  
Vol 28 (2) ◽  
pp. 101-109
Keyword(s):  
Simulated Annealing ◽  
Software Testing ◽  
Simulated Annealing Algorithm ◽  
Search Algorithm ◽  
Fault Localization ◽  
Good Effect ◽  
Test Case ◽  
Genetic Simulated Annealing Algorithm ◽  
Starting Point ◽  
Annealing Algorithm

Software testing is an important stage in the software development process, which is the key to ensure software quality and improve software reliability. Software fault localization is the most important part of software testing. In this paper, the fault localization problem is modeled as a combinatorial optimization problem, using the function call path as a starting point. A heuristic search algorithm based on hybrid genetic simulated annealing algorithm is used to locate software defects. Experimental results show that the fault localization method, which combines genetic algorithm, simulated annealing algorithm and function correlation analysis method, has a good effect on single fault localization and multi-fault localization. It greatly reduces the requirement of test case coverage and the burden of the testers, and improves the effect of fault localization.

scholarly journals Optimizing Crosstalk in Optical NoC through Heuristic Fusion Mapping

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 1006
Author(s):  
Xinhao Shi ◽  
Ning Wu ◽  
Fen Ge ◽  
Fang Zhou ◽  
Muhammad Rehan Yahya
Keyword(s):  
Simulated Annealing Algorithm ◽  
Interconnection Network ◽  
Optical Network ◽  
Optical Signal ◽  
Crosstalk Noise ◽  
Mapping Algorithm ◽  
Annealing Algorithm ◽  
On Chip ◽  
Mapping Scheme ◽  
Better Than

Optical network-on-chip is considered to be a promising technology to solve the problems of low bandwidth and high latency in the traditional interconnection network. However, due to the inevitable leakage of optical devices, the optical signal will receive crosstalk noise during transmission. In this paper, a heuristic fusion mapping algorithm PSO_SA for crosstalk optimization is proposed. First, the initial optimal mapping is obtained by particle swarm optimization, and then the local optimization of the mapping scheme is removed by combining with simulated annealing algorithm. The experimental results show that the crosstalk optimization performance of PSO_SA algorithm is better than that of GA algorithm in 263 dec, Wavelet, DVOPD and other applications, and the maximum optimization degree is 28.7%.

scholarly journals Composite Differential Search Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Bo Liu
Keyword(s):  
Convergence Rate ◽  
Optimization Problem ◽  
Search Algorithm ◽  
Search Algorithms ◽  
Control Parameters ◽  
Original Algorithm ◽  
New Space ◽  
Random Method ◽  
Better Than

Differential search algorithm (DS) is a relatively new evolutionary algorithm inspired by the Brownian-like random-walk movement which is used by an organism to migrate. It has been verified to be more effective than ABC, JDE, JADE, SADE, EPSDE, GSA, PSO2011, and CMA-ES. In this paper, we propose four improved solution search algorithms, namely “DS/rand/1,” “DS/rand/2,” “DS/current to rand/1,” and “DS/current to rand/2” to search the new space and enhance the convergence rate for the global optimization problem. In order to verify the performance of different solution search methods, 23 benchmark functions are employed. Experimental results indicate that the proposed algorithm performs better than, or at least comparable to, the original algorithm when considering the quality of the solution obtained. However, these schemes cannot still achieve the best solution for all functions. In order to further enhance the convergence rate and the diversity of the algorithm, a composite differential search algorithm (CDS) is proposed in this paper. This new algorithm combines three new proposed search schemes including “DS/rand/1,” “DS/rand/2,” and “DS/current to rand/1” with three control parameters using a random method to generate the offspring. Experiment results show that CDS has a faster convergence rate and better search ability based on the 23 benchmark functions.

scholarly journals Hierarchical framework for coordinate optimization of train timetable and electric motor train unit circulation plan

2017 ◽  
Vol 9 (7) ◽  
pp. 168781401770579
Author(s):  
Chao Lu ◽  
Leishan Zhou ◽  
Jinjin Tang ◽  
Ran Chen
Keyword(s):  
Electric Motor ◽  
Simulated Annealing Algorithm ◽  
Optimal Solution ◽  
Computation Time ◽  
Tree Construction ◽  
Total Travel Time ◽  
Annealing Algorithm ◽  
Increasing Demand ◽  
Main Model

To meet the increasing demand for improving railway service quality while using the precious mobile resources reasonably and economically, this research proposes a hierarchical approach that integrates the model for constructing an efficient electric motor train unit circulation plan into the model for optimized timetable design without predefining timetable details. A simulated annealing algorithm for solving the timetabling (main) model is designed, in which the neighborhood system is pretreated. A special tree construction–based branch-and-bound algorithm is improved for solving the electric motor train unit circulation planning (sub)model. The results of the numerical experiment verify the effectiveness of the proposed method. Specifically, compared to the randomly generated initial solution, the optimal solution obtained by the proposed methods reduces the total travel time by 686 min and reduces the number of electric motor train units by 5. The number of electric motor train units needed by the proposed method is on average at least two less than the method that handles the problem in a sequential way. Railway operators can implement this approach for balancing the efficiency of timetable and the quality of electric motor train unit circulation plan within a reasonable computation time when scheduling trains in railways.

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