• Advances in Computational Design
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• v.5 no.4
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• pp.381-396
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• 2020

This study aimed to develop an optimal model of transportation for people with disabilities. To achieve this goal, powers of research and design should be involved, including CAD software. This paper investigates both: the concept of optimal model of transportation for people with disabilities (functional, ergonomic, constructive, technological and aesthetic solutions included); and its implementation as a fully-fledged 3D-model designed in SolidWorks environment. The optimal model of transportation is complex and consists of two objects. The first object is for indoors that is a wheelchair, the second one is for street driving that is an individual vehicle. The optimal model of transportation is universal and multifunctional, which have become possible with parametric feature-based approach utilized in SolidWorks.

• Journal of Korean Institute of Industrial Engineers
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• v.16 no.1
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• pp.27-36
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• 1990

This study deals with the dynamic transportation-inventory model for a single product from which the optimal procurement quantities and the transportation modes are determined simultaneously over a finite planning horizon. Moreover, it covers the situation where quantity discounts are applied to the transportation cost as well as the purchase cost and disposals of the excess are possible at the end of each period. For a relevant mathematical model formulated, the theorems and properties of an optimal solution are discussed to present the efficient algorithm. A numerical example is solved to illustrate the algorithm developed.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.46-54
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• 2023

To improve the railway transportation capacity and maximize the benefits of railway transportation, a method for layout optimization of railway transportation route based on deep convolution neural network is proposed in this study. Considering the transportation cost of railway transportation and other factors, the layout model of railway transportation route is constructed. Based on improved ant colony algorithm, the layout model of railway transportation route was optimized, and multiple candidate railway transportation routes were output. Taking into account external information such as regional information, weather conditions and actual information of railway transportation routes, optimization of the candidate railway transportation routes obtained by the improved ant colony algorithm was performed based on deep convolution neural network, and the optimal railway transportation routes were output, and finally layout optimization of railway transportation routes was realized. The experimental results show that the proposed method can obtain the optimal railway transportation route, the shortest transportation length, and the least transportation time, maximizing the interests of railway transportation enterprises.

• IE interfaces
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• v.20 no.2
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• pp.204-215
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• 2007

This paper addresses vehicle routing planning in freight container transportation systems where a number of loaded containers are to be delivered to their destination places. The system under consideration is static in that all transportation requirements are predetermined at the beginning of a planning horizon. A two-phased procedure is presented for freight container transportation. In the first phase, the optimal model is presented to determine optimal total time to perform given transportation requirements and the minimum of number of vehicles required. Based on the results from the optimal model, in the second phase, ASA(Accelerated Simulated Annealing) algorithm is presented to perform all transportation requirements with the least number of vehicles by improving initial vehicle routing planning constructed by greedy method. It is found that ASA algorithm has an excellent global searching ability through various experiments in comparison with existing methods.

• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.193-206
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• 2002

A signal optimization model is proposed by applying the Cell-Transmission Model(CTM) as an embedded traffic flow model to estimate a system-optimal signal timing plan in a transportation network composed of signalized intersections. Beyond the existing signal-optimization models, the CTM provides appropriate theoretical and practical backgrounds to simulate oversaturation phenomena such as shockwave, queue length, and spillback. The model is formulated on the Mixed-Integer Programming(MIP) theory. The proposed model implies a system-optimal in a sense that traffic demand and signal system cooperate to minimize the traffic network cost: the demand departing from origins through route choice behavior until arriving at destinations and the signal system by calculating optimal signal timings considering the movement of these demand. The potential of model's practical application is demonstrated through a comparison study of two signal control strategies: optimal and fixed signal controls.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.159-166
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• 2006

The aim of synchronization of production and transportation planning in the supply chain is to increase the flexibility and to decrease various costs. The suggested model in this study synchronizes the timing to supply to a downstream manufacturer directly after production and to be consumed in a downstream manufacturer right after receipt. This model deals with the frequent delivery in small amount which is a new trend of the transportation not governed the economy of scale principle. Moreover, various types of transportation governed by the economy of scale principle or not are considered. Then, the two-phase mathematical model is suggested to obtain optimal job sequence and production quantity for each tasks. But, it is difficult to gain optimal solutions if there is a transportation governed by the economy of scale principle in the supply chain, or the size of the problem is increased. Thus, heuristic algorithms based on simulated annealing and genetic algorithm are suggested to find good solutions in the reasonable time.

• IE interfaces
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• v.16 no.2
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• pp.174-184
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• 2003

This paper addresses a fleet operation planning problem for a static freight container transportation system in which all the transportation requirements are predetermined at the beginning of a planning horizon. In the transportation system under consideration, a number of loaded containers are to be moved between container storage yards. An optimal fleet planning model is used to determine the minimum number of vehicles required. Based on the results from the optimal model, a tabu-search based algorithm is presented to perform a given transportation requirements with the least number of vehicles. The performance of the new procedure is evaluated through some experiments in comparison with two existing methods, and the it is found that our procedure produces good-quality solutions.

• Journal of Korean Society of Transportation
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• v.13 no.4
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• pp.5-29
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• 1995

Advanced Traveler Inoformation Systems*ATIS) , as a subsystem of ITS influence the travel choices of dreivers by providing them with historical, real-time and predictive information to supprot travel decisions and consequently improves the speed and quality of travel. For thesuccessul accomplishment of ATIS, the time-dependent variations of traffic in a road network and travel times of vehicles during their journey must be predicted . The purpose of this study is to evaluate the past developments in the dynamic route choice models and to apply the instantaneous dynamic user optimal route choice model. recently formulated with flow propagation constraints by Ran, Boyce and LeBlanc, to the real transportation network of Seocho-Ku in Seoul. As input data for this application, the time-dependent travel rates are estimated and the link travel time function is derived. The modelis validated from three view points : the efficiency of model itself the ability to predict traffic volume and travel time on links, and the optimal traffic control.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.1
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• pp.157-165
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• 1998

This paper considers the single-product production and transportation problem with discrete time, dynamic demand and finite time horizon, an extension of classical dynamic lot-sizing model. In the model, multiple freight container types are allowed as the transportation mode and each order (product) placed in a period is shipped immediately by containers in the period. Moreover, each container has type-dependent carrying capacity restriction and at most one container type is allowed in each shipping period. The unit freight cost for each container type depends on the size of its carrying capacity. The total freight cost is proportional to the number of each container type employed. Such a freight cost is considered as another set-up cost. Also, it is assumed in the model that production and inventory cost functions are dynamically concave and backlogging is not allowed. The objective of this study is to determine the optimal production policy and the optimal transportation policy simultaneously that minimizes the total system cost (including production cost, inventory holding cost, and freight cost) to satisfy dynamic demands over a finite time horizon. In the analysis, the optimal solution properties are characterized, based on which a dynamic programming algorithm is derived. The solution algorithm is then illustrated with a numerical example.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.7
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• pp.750-755
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• 2014

Product shortage which causes backordering and/or lost sales cost is very popular in chemical industries, especially in commodity polymer business. This study deals with backordering cost in the supply chain optimization model under the framework of process-inventory network. Classical economic order quantity model with backordering cost suggested optimal time delay and lot size of the final product delivery. Backordering can be compensated by advancing production/transportation of it or purchasing substitute product from third party as well as product delivery delay in supply chain network. Optimal solutions considering all means to recover shortage are more complicated than the classical one. We found three different solutions depending on parametric range and variable bounds. Optimal capacity of production/transportation processes associated with the product in backordering can be different from that when the product is not in backordering. The product shipping cycle time computed in this study was smaller than that optimized by the classical EOQ model.