• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.3
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• pp.62-69
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• 2006

Vehicle routing problem with time windows is determined each vehicle route in order to minimize the transportation costs. All delivery points in geography have various time restriction in camparision with the basic vehicle routing problem. Vechicle routing problem with time windows is known to be NP-hard, and it needs a lot of computing time to get the optimal solution, so that heuristics are more frequently developed than optimal algorithms. This study aims to develop a heuristic method which combines guided local search with a tabu search in order to minimize the transportation costs for the vehicle routing assignment and uses ILOG programming library to solve. The computational tests were performed using the benchmark problems.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.933-941
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• 2010

KORAIL has improved profitability through abolition of nonprofitable route and withdraw rolling stocks, operated at that route. as a part of that process, most sections of commuters' train are gone. presently, gyeongui-line and gyeongwon-line's commuter's trains are operated. Despite the abolition, there are demands for commuters' train. so, nonprofitable route operation policies are needed to meet the demands and connect seamlessly to KTX. In this study, we consider the overall operation policies and problems of commuters' train in the past. and then, we analyze foreign nonprofitable route, connected with high speed train, operation policies and search for the development suggestions for applying to the nonprofitable route between Iksan - jeonju section at Honam and joenra line.

• Proceedings of the KOR-KST Conference
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• 2000.02a
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• pp.25-47
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• 2000

In route guidance systems fastest-path routing has typically been adopted because of its simplicity. However, empirical studies on route choice behavior have shown that drivers use numerous criteria in choosing a route. The objective of this study is to develop computationally efficient algorithms for identifying a manageable subset of the nondominated (i.e. Pareto optimal) paths for real-time vehicle routing which reflect the drivers' preferences and route choice behaviors. We propose two pruning algorithms that reduce the search area based on a context-dependent linear utility function and thus reduce the computation time. The basic notion of the proposed approach is that ⅰ) enumerating all nondominated paths is computationally too expensive, ⅱ) obtaining a stable mathematical representation of the drivers' utility function is theoretically difficult and impractical, and ⅲ) obtaining optimal path given a nonlinear utility function is a NP-hard problem. Consequently, a heuristic two-stage strategy which identifies multiple routes and then select the near-optimal path may be effective and practical. As the first stage, we utilize the relaxation based pruning technique based on an entropy model to recognize and discard most of the nondominated paths that do not reflect the drivers' preference and/or the context-dependency of the preference. In addition, to make sure that paths identified are dissimilar in terms of links used, the number of shared links between routes is limited. We test the proposed algorithms in a large real-life traffic network and show that the algorithms reduce CPU time significantly compared with conventional multi-criteria shortest path algorithms while the attributes of the routes identified reflect drivers' preferences and generic route choice behaviors well.

• Journal of Korean Society of Transportation
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• v.20 no.1
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• pp.65-76
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• 2002

This study is realized using fuzzy evaluation and AHP(the analytic hierarchy process) for the optimum search of traffic route and estimated by the quantitative analysis in the vague subjective judgement. It is different from classical route search and noticed thinking method of human. Appraisal element, weight, appraisal value of route is extracted from basic of the opinion gathering fur the driving expert and example of route model was used for the finding of practice utility. Model assessment was performed attribute membership function making of estimate element, estimate value setting, weight define by the AHP, non additive presentation of weight according to $\lambda$-fuzzy measure, Choquet fuzzy integral.

• Journal of the Korea Institute of Building Construction
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• v.17 no.4
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• pp.369-375
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• 2017

This study suggests PSO(Particle Swarm Optimization) algorithm that optimizes the snowplow route allocation and the location of the snow control material storage to improve the efficiency in snow removal works. The modified PSO algorithm for improving the search capacity is proposed, and this study suggests the solution representation, the parameter setting, and the fitness function for the given optimization problems. Computational experiments in real-world case are carried out to justify the proposed method and compared with the traditional PSO algorithms. The results show that the proposed algorithms can find the better solution than the traditional PSO algorithms by searching for the wider solution space without falling into the local optima. The finding of this study is efficiently employed to solve the optimization of the snowplow route allocation by minimizing the workload of each snowplow to search the location of the snow control material storage as well.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.303-313
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• 2019

After a disaster happens in urban areas, many people need support for a quick evacuation. This work aims to develop a method for the calculation of the most feasible evacuation route inside buildings. In the methodology we simplify the geometry of the structural and non structural elements from the BIM (Building Information Modeling) to store them in a spatial database which follows standards to support vector data. Then, we apply the multicriteria analysis with the allocation of prioritization values and weight factors validated through the AHP (Analytic Hierarchy Process), in order to obtain the Importance Index S(n) of the elements. The criteria consider security conditions and distribution of the building's facilities. The S(n) is included as additional heuristic data for the calculation of the evacuation route through an algorithm developed as a variant of the $A^*$ pathfinding, The experimental results in the simulation of evacuation scenarios for vulnerable people in healthy physical conditions and for the elderly group, shown that the conditions about the wide of routes, restricted areas, vulnerable elements, floor roughness and location of facilities in the building applied in the multicriteria analysis has a high influence on the processing of the developed variant of $A^*$ algorithm. The criteria modify the evacuation route, because they considers as the most feasible route, the safest instead of the shortest, for the simulation of evacuation scenarios for people in healthy physical conditions. Likewise, they consider the route with the location of facilities for the movement of the elderly like the most feasible in the simulation of evacuation route for the transit of the elderly group. These results are important for the assessment of the decision makers to select between the shortest or safest route like the feasible for search and rescue activities.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.4
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• pp.469-478
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• 2012

This study aims to discover the optimal pipe layout for a ship, which generally needs a lot of time, efforts and experiences. Genetic algorithm was utilized to search for the optimum. Here the optimum stands for the minimum pipe length between two given points. Genetic algorithm is applied to planar pipe layout problems to confirm plausible and efficiency. Sub-programs are written to find optimal layout for the problems. Obstacles are laid in between the starting point and the terminal point. Pipe is supposed to bypass those obstacles. Optimal layout between the specified two points can be found using the genetic algorithm. Each route was searched for three case models in two-dimensional plane. In consequence of this, it discovered the optimum route with the minimized distance in three case models. Through this study, it is possible to apply optimization of ship pipe route to an actual ship using genetic algorithm.

• Journal of the Korea Safety Management & Science
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• v.14 no.3
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• pp.159-166
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• 2012

A*algorithm is highly useful to search the shortest route to the destination in the evacuation simulation. For this reason, A*algorithm is used to evaluate the evacuation experiment by the computer simulation. However there are some problems to analyze the outcome in relation to the reality. Because all the people in the building are not well-informed of the shortest route to the exit. And they will not move to the disaster spot though it is shortest route to the exit. Therefore, evacuation simulation program based on A*algorithm raise a problem of bottleneck phenomenon and dangerous result by damage surrounding the disaster spot. The purpose of this research is to prove the necessity for dispersion evacuation simulation by Multi agent system to solve the problems of the existing evacuation simulation program based on A*algorithm.

• Journal of Intelligence and Information Systems
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• v.2 no.1
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• pp.93-107
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• 1996

A flexible flow line(FFL) consists of several groups of identical machines. All work-orders flow along the same path through successive machine groups. Thus, we emphasized the balancing of workloads between machine groups in order to maximize total productivity. On the other hand, many different types of work-orders, in varying batch or lot sizes, are produced simultaneously. The mix of work-orders, their lot sizes, and the sequence in which they are produced affect the amount of workload. However, the work-orders and their lot sizes are prefixed and cannot be changed. Because of these reasons, we have developed an optimal route selection model using heuristic search and Min-Max algorithm for balancing the workload between machine groups in the FFL.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.146-149
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• 2000

In this paper, Computer Colour Matching and Kitchen System (CCMKS) is developed on the basis of delphi package and one-chip processor with fuzzy-PID control. CCMKS will be widely used in the colour dyeing industry as an integrated colour matching and dispensing system which have more advantages than the conventional matching or dispensing system, when controlling the real dyeing processes. Delphi is utilized in making database and search/matching routes. The developed matching function reduces the search and matching time to about one third. One-chip processor is designed and manufactured for the distributed control of three-phase induction motors. Fuzzy-PID control is applied to the speed control of three-phase induction motors for a very precise weight of colour at CCMKS. The developed kitchen function decreases the dispensing time to about one twentieth. The experimental results show CCMKS has more excellent search time, more precise weight and much high fidelity than conventional colour matching or dispensing system, in the performance.