• Journal of Korean Institute of Industrial Engineers
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• v.30 no.4
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• pp.346-354
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• 2004

Most industrial logistic systems have focused on carrying products from manufacturers or distribution centers to customers. In recent years, they are faced with the problem of integrating reverse flows into their transportation systems. In this paper, we address the vehicle routing problems with mixed delivery and pick-up(VRPMDP). Mixed operation of delivery and pick-up during a vehicle tour requires rearrangement of the goods on board. The VRPMDP considers the reshuffling time of goods at customers, hard time windows, and split operation of delivery and pick-up. We construct a mixed integer mathematical model and propose a new genetic algorithm named GAMP for VRPMDP. Computational experiments on various types of test problems are performed to evaluate GAMP against the modified Dethloff's algorithm. The results show that GAMP reduces the total vehicle operation time by 5.9% on average, but takes about six times longer computation time.

• Korean Management Science Review
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• v.29 no.1
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• pp.89-99
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• 2012

In this paper, we deal with the dual-depot heterogeneous vehicle routing problem with simultaneous delivery and pick up(DH-VRPSDP) in reverse logistics. The DH-VRPSDP is a problem of designing vehicle routes in a day of given vehicle to minimize the sum of fixed cost and variable cost over the planning horizon. Each customer can be visited only once according to the service combinations of that customer. Due to the complexity of the problem, we suggest a heuristic algorithm in which an initial solution is obtained by changing the customer and the vehicle simultaneously and then it is improved. A performance of the proposed algorithm was compared to both well-known results and new test problems.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.1
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• pp.153-165
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• 2009

This paper apollos an ant colony system (ACS) for the vehicle routing problem with time window (VRPTW). The VRPTW is a generalization of the VRP where the service of a customer can begin within the time windows defined by the earliest and latest times when the customer will permit the start of service. The ACS has been applied effectively in geographical environment such as TSP or VRP by meta-heuristic that imitate an ant's biologic special duality in route construction, 3 saving based ACS (SB-ACS) is introduced and its solution is improved by local search. Through iterative precesses, the SB-ACS is shown to drive the best solution. The algorithm has been tested on 56 Solomon benchmarking problems and compared to the best-known solutions on literature. Experimental results shows that SB-ACS algorithm could obtain food solution in total travel distance minimization.

• Journal of the Korean Operations Research and Management Science Society
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• v.36 no.1
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• pp.27-38
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• 2011

In this paper, we deal with the periodic heterogeneous fleet vehicle routing problem (PHVRP). PHVRP is a problem of designing vehicle routes in each day of given period to minimize the sum of fixed cost and variable cost over the planning horizon. Each customer can be visited once or more times over the planning horizon according to the service combinations of that customer. Due to the complexity of the problem, we suggest a heuristic algorithm in which an initial solution is obtained by assigning the customer-day and the customer-car simultaneously and then it is improved. A performance of the proposed algorithm was compared to both well-known results and new test problems.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1740-1745
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• 2006

This paper is concerned with a novel heuristic algorithm for the multi-trip vehicle routing problem with time windows. The objective function is the minimization of total vehicle operating time, fixed cost of vehicle and the minimization of total lateness of customer. A mixed integer programming formulation and a heuristic algorithm for a practical use are suggested. A heuristic algorithm is constructed two phases such as clustering and routing. Clustering is progressed in order to assign appropriate vehicle to customer, and then vehicle trip and route are decided considering traveling distance and time window. It is shown that the suggested heuristic algorithm gives good solutions within a short computation time by experimental result.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1733-1739
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• 2006

This paper is concerned with multi-objective vehicle routing problem(VRP), in which objective of this problem is to minimize the total operating time of vehicles and the total tardiness of customers. A mixed integer programming formulation and a heuristic for practical use are suggested. The heuristic is based on the route-perturbation and route-improvement method(RPRI). Performances are compared with other heuristic appeared in the previous literature using the modified bench-mark data set. It is shown that the suggested heuristic give good solution within a short computation time by computational experiment.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.179-186
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• 2006

There was a lot of research to integration of the transshipment and inventory problem in supply chain. Such a integration of inventory and transshipment problem called IRP (Inventory Routing Problem). We consider a distribution problem in which a set of products has to be shipped from a supplier to several retailers in a given planning horizon. Transshipment from the supplier to the retailer is performed by vehicles of limited capacity. Each retailer determines replenishment leadtime and order quantity with buffer management. A supplier determines optimal vehicle routing in supply chain. We suggest a heuristic algorithm which be used TOC buffer management in a replenishment problem and a tabu search algorithm in VRP (Vehicle Routing Problem).

• 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.

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.2
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• pp.160-170
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• 2009

This paper studies a vehicle routing problem variant which considers customers to require simultaneous delivery and pick-up under time windows(VRPSDP-TW). The objective of this paper is to minimize the total travel distance of routes that satisfy both the delivery and pick-up demand. We propose a heuristic algorithm for solving the VRPSDP-TW, based on the ant colony system(ACS). In route construction, an insertion algorithm based ACS is applied and the interim solution is improved by local search. Through iterative processes, the heuristic algorithm drives the best solution. Experiments are implemented to evaluate a performance of the algorithm on some test instances from literature.

• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.2
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• pp.53-66
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• 1989

The Public Vehicle Routing Problem (PVRP) is to find the minimum total cost routes of M or less Public-Vehicles to traverse the required arcs(streets) at least once, and return to their starting depot on a directed network. In this paper, first, a mathematical model is formulated as minimal cost flow model with illegal subtour elimination constraints, and with the fixed cost and routing cost as an objective function. Second, an efficient branch and bound algorithm is developed to obtain an exact solution. A subproblem in this method is a minimal cost flow problem relaxing illegal subtour elimination constraints. The branching strategy is a variable dichotomy method according to the entering nonrequired arcs which are candidates to eneter into an illegal subtour. To accelerate the fathoming process, a tighter lower bound of a candidate subproblem is calculated by using a minimum reduced coast of the entering nonrequired arcs. Computational results based on randomly generated networks report that the developed algorithm is efficient.