• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.33 no.2
• /
• pp.81-88
• /
• 2010

This paper presents an application of heuristic approach to problem of designing reliable network expansion. The problem essentially consists in finding the network topology that satisfies given set of reliability constraints. To efficiently solve the problem, a scatter search approach is proposed. The results of the two experiments show that scatter search is a more suitable approach for finding a good solution or near optimal solution in comparison with genetic algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.34 no.1
• /
• pp.33-41
• /
• 2011

This paper considers a topological optimization of a network design with mean packet delay and node connectivity constraints. The objective is to find the topological layout of links, at minimal cost. This Problem is known to be NP-hard. To efficiently solve the problem, a scatter search algorithm is proposed. An illustrative example is used to explain and test the proposal approach. Experimental results show evidence that the proposal approach performs more efficiently for finding a good solution or near optimal solution in comparison with a genetic approach.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.31 no.1
• /
• pp.101-107
• /
• 2008

This paper considers a topological optimization of a computer network design with a reliability constraint. The objective is to find the topological layout of links, at minimal cost, under the constraint that the network reliability is more than a given reliability. To efficiently solve the problem, a scatter search approach is proposed. Two illustrative examples are used to explain and test the proposed approach. Experimental results show evidence that the proposed approach performs more efficiently for finding a good solution or near optimal solution in comparison with a genetic algorithm approach.

• Journal of Ocean Engineering and Technology
• /
• v.17 no.6
• /
• pp.38-46
• /
• 2003

Aim of this article is to propose Micro-Genetic Simulated Annealing (${\mu}GSA$) as a hybrid metaheuristics approach to find the global optimum of nonlinear optimisation problems. This approach combines the features of modern metaheuristics such as micro-genetic algorithm (${\mu}GAs$) and simulated annealing (SA) with the general robustness of parallel exploration and asymptotic convergence, respectively. Therefore, ${\mu}GSA$ approach can help in avoiding the premature convergence and can search for better global solution, because of its wide spread applicability, global perspective and inherent parallelism. For the superior performance of the ${\mu}GSA$, the five well-know benchmark test functions that were tested and compared with the two global optimisation approaches: scatter search (SS) and hybrid scatter genetic tabu (HSGT) approach. A practical application to structural sandwich panel is also examined by optimism the weight function. From the simulation results, it has been concluded that the proposed ${\mu}GSA$ approach is an effective optimisation tool for soloing continuous nonlinear global optimisation problems in suitable computational time frame.

• International Journal of Computer Science & Network Security
• /
• v.23 no.6
• /
• pp.193-201
• /
• 2023

In this paper, we consider the maximum scatter traveling salesman problem (MSTSP), a travelling salesman problem (TSP) variant. The problem aims to maximize the minimum length edge in a salesman's tour that travels each city only once in a network. It is a very complicated NP-hard problem, and hence, exact solutions can be found for small sized problems only. For large-sized problems, heuristic algorithms must be applied, and genetic algorithms (GAs) are found to be very successfully to deal with such problems. So, this paper develops a hybrid GA (HGA) for solving the problem. Our proposed HGA uses sequential sampling algorithm along with 2-opt search for initial population generation, sequential constructive crossover, adaptive mutation, randomly selected one of three local search approaches, and the partially mapped crossover along with swap mutation for perturbation procedure to find better quality solution to the MSTSP. Finally, the suggested HGA is compared with a state-of-art algorithm by solving some TSPLIB symmetric instances of many sizes. Our computational experience reveals that the suggested HGA is better. Further, we provide solutions to some asymmetric TSPLIB instances of many sizes.

• Industrial Engineering and Management Systems
• /
• v.8 no.3
• /
• pp.171-180
• /
• 2009

Population learning algorithm (PLA) is a population-based method that was inspired by the similarities to the phenomenon of social education process in which a diminishing number of individuals enter an increasing number of learning stages. The study aims to develop a framework that repeatedly applying the PLA to solve the discrete resource constrained project scheduling problem with two objectives: minimizing project makespan and renewable resource availability, which are two most common concerns of management when a project is being executed. The PLA looping framework will provide a number of near Pareto optimal schedules for the management to make a choice. Different improvement schemes and learning procedures are applied at different stages of the process. The process gradually becomes more and more sophisticated and time consuming as there are less and less individuals to be taught. An experiment with ProGen generated instances was conducted, and the results demonstrated that the looping framework using PLA outperforms those using genetic local search, particle swarm optimization with local search, scatter search, as well as biased sampling multi-pass algorithm, in terms of several performance measures of proximity. However, the diversity using spread metric does not reveal any significant difference between these five looping algorithms.

• Proceedings of the KOSOMBE Conference
• /
• v.1991 no.05
• /
• pp.9-12
• /
• 1991

The correlation search method yields velocity information by tracking scatter patterns between medical image frames. The displacement vector between a target region and the best correlated search region indicates the magnitude and direction of the inter-frame motion of that particular region. However, if the noise sources in the target region and the search region are correlated Gaussian, then the cross-correlation technique fails to work well because it estimates the cross-correlation of both signals and noises. In this paper we develop a new correlation search method which seeks the best correlated third-order statistics between a target and the search region to suppress the effect of correlated Gaussian noise sources. Our new method yields better estimations of velocity than the conventional cross-correlation method.

• International conference on construction engineering and project management
• /
• 2015.10a
• /
• pp.221-225
• /
• 2015

To hoist construction workers to their working space is directly related to the productivity of building construction since hoisting tasks are carried out during the working time. In order to reduce hoisting time in the condition that the number of construction lift-cars is limited, various types of the lift-cars group operation plans such as zoning and sky-lobby have been applied. However, previous researches on them cannot be compared in the performance due to their methodological limitation, discrete-event simulation methods, and cannot be find better solution to increase the performance. Therefore, this research proposed the simulation-based optimization model combining the agent-based simulation method to the scatter search optimization methods. Using the proposed model, this paper carried out the comparison analysis on the performance of typical operation plans and also optimize an operation plans by controlling the service range of lift-cars, the size and number of service zones. In this case study, it is verified that better alternatives than typical operation plans can be exists and it is possible to increase the productivity of building construction.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.9
• /
• pp.1600-1604
• /
• 2010

This paper presents the optimum design of the brushless motor to maximize the output power per weight considering the design parameter tolerance. The optimization is proceeded by commercial software that is adopted the scatter-search algorithm and the characteristic analysis is conducted by FEM. The stochastic optimum design results are compared with those of the deterministic optimization method. We can verify that the results of the stochastic optimization is superior than that of deterministic optimization.

• Healthcare Informatics Research
• /
• v.24 no.4
• /
• pp.300-308
• /
• 2018

Objectives: Prompt detection is a cornerstone in the control and prevention of infectious diseases. The Integrated Disease Surveillance Project of India identifies outbreaks, but it does not exactly predict outbreaks. This study was conducted to assess temporal correlation between Google Trends and Integrated Disease Surveillance Programme (IDSP) data and to determine the feasibility of using Google Trends for the prediction of outbreaks or epidemics. Methods: The Google search queries related to malaria, dengue fever, chikungunya, and enteric fever for Chandigarh union territory and Haryana state of India in 2016 were extracted and compared with presumptive form data of the IDSP. Spearman correlation and scatter plots were used to depict the statistical relationship between the two datasets. Time trend plots were constructed to assess the correlation between Google search trends and disease notification under the IDSP. Results: Temporal correlation was observed between the IDSP reporting and Google search trends. Time series analysis of the Google Trends showed strong correlation with the IDSP data with a lag of -2 to -3 weeks for chikungunya and dengue fever in Chandigarh (r > 0.80) and Haryana (r > 0.70). Malaria and enteric fever showed a lag period of -2 to -3 weeks with moderate correlation. Conclusions: Similar results were obtained when applying the results of previous studies to specific diseases, and it is considered that many other diseases should be studied at the national and sub-national levels.