• IE interfaces
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• v.24 no.1
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• pp.51-57
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• 2011

The traveling purchaser problem (TPP) is a generalization of the well-known traveling salesman problem (TSP), which has many real-world applications such as purchasing the required raw materials for the manufacturing factories and the scheduling of a set of jobs over some machines, and many others. In the last decade, TPP has received some attention of the researchers in the operational research area. However, all of the past researches for TPP are restricted on a single purchaser (vehicle). It could be the limitation to solve the real world problem. The purpose of this paper is to suggest the capacitated multiple TPP (CMTPP). It could be used in inbound logistics optimization in supply chain management area and many others. Since TPP is known as NP-hard, we also developed the heuristic algorithm to solve the CMTPP.

• Journal of the Korea Safety Management & Science
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• v.15 no.2
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• pp.193-204
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• 2013

The growing logistics strategy of a company is to optimize their vehicle route scheduling in their supply chain system. It is very important to analyze for continuous pickups and delivery vehicle scheduling. This paper is a computational study to investigate the effectiveness of continuous pickups and delivery vehicle routing problems. These scheduling problems have 3 subproblems; Inbound Vehicle Routing Problem with Makespan and Pickup, Line-haul Network Problem, and Outbound Vehicle Routing Problem with Delivery. In this paper, we propose 5 heuristic Algorithms; Selecting Routing Node, Routing Scheduling, Determining Vehicle Type with Number and Quantity, and Modification Selecting Routing Node. We apply these Algorithms to S vehicle company. The results of computational experiments demonstrate that proposed methods perform well and have better solutions than other methods considering the basic time and due-date.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.3
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• pp.233-242
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• 2015

This paper analyzes a multi-product inbound lot-sizing and outbound dispatching problem with multi-vehicle types in a third-party logistics distribution center. The product must be delivered to the customers within the delivery time window and backlogging is not allowed. Replenishing orders are shipped by several types of vehicles with two types of the freight costs, i.e., uniform and decreasing, are considered. The objective of this study is to determine the lot-size and dispatching schedules to minimize the total cost with the sum of inbound and outbound transportation and inventory costs over the entire time horizon. In this study, we mathematically derive a mixed-integer programming model and propose a genetic algorithm (GA1) based on a local search heuristic algorithm to solve large-scale problems. In addition, we suggest a new genetic algorithm (GA2) with an adjusting algorithm to improve the performance of GA1. The basic mechanism of the GA2 is to provide an unidirectional partial move of products to available containers in the previous period. Finally, we analyze the results of GA1 and GA2 by evaluate the relative performance using the gap between the objective values of CPLEX and the each algorithm.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.4
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• pp.331-341
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• 2011

This paper considers an inbound lot-sizing and outbound dispatching problem for a single product in a thirdparty logistics (3PL) distribution center. Demands are dynamic and finite over the discrete time horizon, and moreover, each demand has a delivery time window which is the time interval with the dates between the earliest and the latest delivery dates All the product amounts must be delivered to the customer in the time window. Ordered products are shipped by multiple vehicle types and the freight cost is proportional to the vehicle-types and the number of vehicles used. First, we formulate a mixed integer programming model. Since it is difficult to solve the model as the size of real problem being very large, we design a conventional genetic algorithm with a local search heuristic (HGA) and an improved genetic algorithm called adaptive genetic algorithm (AGA). AGA spontaneously adjusts crossover and mutation rate depending upon the status of current population. Finally, we conduct some computational experiments to evaluate the performance of AGA with HGA.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.471-480
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• 2016

The purpose of this study is to identify the intent of the Total Amount of Vehicles policy that is enforced during the two summer season months (July and August) in U-do and the consequent problems after its implementation. We propose a basic direction for the policy to be sustainable. The average daily number of vehicles visiting was 645 in July 2015 and 953 in August 2015. As these numbers exceed the limit of 605, serious transportation problems such as traffic congestion and traffic accidents have occurred in U-do. We propose that the future direction of the policy is set forth as follows. First, mandatory reporting and the use of insurance, such as motorcycles, will have to be introduced along with measures to regulate violations. Second, a scheme needs to be introduced to enhance the total Amount of Vehicle policy and the number of inbound vehicles. Finally, public transportation cooperatives that are directly managed by local residents need to be established and an Eco-friendly vehicles dissemination policy introduced.

• Journal of the Korea Safety Management & Science
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• v.18 no.4
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• pp.107-114
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• 2016

The efficiency of the purchasing and procurement logistics is important in automotive industry. The rationalization of production system is directly impact on productivity and quality. For this reason importance of logistics is high. Despite we are continuously making effort, our country are still below the level than developed country on logistics efficiency. Rising labor costs is an important factor in increasing logistics costs. So workforce reduction in logistics department is a large part. We deal with A-company inbound logistics, especially procurement logistics in automotive logistics as research object. So in this study we do research on work load balance about workers. We do research on 1,475 kinds of components in procurement process. We applied work load balance algorithm on chassis, final, sequence, trim warehouses workers. According to number of workers and average M/H, algorithm is applied in two ways. After applied work load balance algorithm we reduced numbers of workers from 28 to 20 and improved worker load balance rate from 47.1% to 93.7%.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.2
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• pp.78-86
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• 2010

The traveling purchaser problem(TPP) is a generalization of the well-known traveling salesman problem(TSP), which has many real-world applications such as purchasing the required raw materials for the manufacturing factories and the scheduling of a set of jobs over some machines, and many others. TPP also could be extended to the vehicle routing problem(VRP) by incorporating additional constraints such as multi-purchaser, capacity, distance and time restrictions. In the last decade, TPP has received some attention of the researchers in the operational research area. However it has not received the equivalent interest as much as TSP and VRP. Therefore, there does not exist a review of the TPP. The purpose of this paper is to review the TPP and to describe solution procedures proposed for this problem. We also introduce the ILP formulation for the multiple TPP(mTPP) which is generalized type of TPP. We compare the system performance according to change from TPP to mTPP.