• Journal of Korean Institute of Industrial Engineers
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• v.25 no.4
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• pp.490-499
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• 1999

Vehicle routing problem(VRP) is known to be NP-hard problem, and good heuristic algorithm needs to be developed. To develop a heuristic algorithm for the VRP, this study suggests a parallel genetic algorithm(PGA), which determines each vehicle route in order to minimize the transportation costs. The PGA developed in this study uses two dimensional array chromosomes, which rows represent each vehicle route. The PGA uses new genetic operators. New mutation operator is composed of internal and external operators. internal mutation swaps customer locations within a vehicle routing, and external mutation swaps customer locations between vehicles. Ten problems were solved using this algorithm and showed good results in a relatively short time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5B
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• pp.464-470
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• 2011

V2V (Vehicle-to-Vehicle) is a special kind of VANET (Vehicular Ad-hoc Network), which has high mobility and frequent topology changes and causes the link breakage problem. To resolve this problem, geographic routing protocols such as greedy forwarding are proposed. However, the greedy forwarding approach selects the node closest to the destination node as the transfer node within the transmission range so that it may cause many problems owing to many intersections and many changes in vehicular traffic in urban areas. The paper proposes a greedy perimeter urban routing (GPUR) algorithm considering the presence of 2-hop neighbor nodes and the road characteristics. Simulation results using ns-2 reveal that the proposed GPUR algorithm significantly reduces the routing error problem and the probability of local maximum than the existing routing protocols.

• IE interfaces
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• v.13 no.3
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• pp.455-461
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• 2000

Logistics systems can be evaluated by how productively distribution center operates, how promptly transportation vehicle dispatches, how efficiently facility layout is, and so on. In this paper, a practical vehicle routing scheme with fixed delivery time and fixed vehicle routes is introduced. The method helps the distribution center reduce logistics cost with respect to dispatching vehicles, and satisfy the customer with pre-determined delivery time window constraints. A case study has shown that the proposed scheme not only generates a feasible schedule with time windows, but also balances material flow in warehouse.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3369-3385
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• 2019

There are various research challenges in vehicular ad hoc networks (VANETs) that need to be focused until an extensive deployment of it becomes conceivable. Design and development of a scalable routing algorithm for VANETs is one of the critical issue due to frequent path disruptions caused by the vehicle's mobility. This study aims to provide a novel road-aware routing protocol for vehicular networks named as Two-level hierarchical Hybrid Road-Aware (THERA) routing for vehicular ad hoc networks. The proposed protocol is designed explicitly for inter-vehicle communication. In THERA, roads are distributed into non-overlapping road segments to reduce the routing overhead. Unlike other protocols, discovery process does not flood the network with packet broadcasts. Instead, THERA uses the concept of Gateway Vehicles (GV) for the discovery process. In addition, a route between source and destination is flexible to changing topology, as THERA only requires road segment ID and destination ID for the communication. Furthermore, Road-Aware routing reduces the traffic congestion, bypasses the single point of failure, and facilitates the network management. Finally yet importantly, this paper also proposes a probabilistical model to estimate a path duration for each road segment using the highway mobility model. The flexibility of the proposed protocol is evaluated by performing extensive simulations in NS3. We have used SUMO simulator to generate real time vehicular traffic on the roads of Gangnam, South Korea. Comparative analysis of the results confirm that routing overhead for maintaining the network topology is smaller than few previously proposed routing algorithms.

• Journal of Intelligence and Information Systems
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• v.15 no.3
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• pp.137-150
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• 2009

This paper proposes the hybrid heuristic method to apply the opportunity time to solve the vehicle routing and scheduling problem with time constraints(VRSPTW). The opportunity time indicates the idle time which remains after the vehicle performs the unloading service required by each customer's node. In this proposed heuristic, we add the constraints to VRSPTW model for the opportunity time. We also obtain the initial solution by applying the cost evaluation function to the insertion strategy considering the opportunity time. In addition, we improve the former result by applying the opportunity time to the tabu search strategy by swapping the customer's node. Finally, we suggest the construction strategies of initial routing which can efficiently acquire the nearest optimal solution from various types of data in terms of geographical condition, scheduling horizon and vehicle capacity. Our experiment show that our heuristic can get the nearest optimal solution more efficiently than the Solomon's I1 heuristic.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.279-282
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• 2001

This paper is concerned with Vehicle Routing Problem to minimize the total delivery waiting time of customers. The delivery waiting time is the time taken to travel from the depot to the customer, which is important for the delivery of the perishing products or foods requiring freshness. We construct a mixed integer linear programming formulation of this problem, and CR(Clustering first Routing second) heuristic and SPH(set partitioning heuristic) are suggested. the results of computational experiments showed that these heuristics find successfully favorable solutions, in much shorter time than optimal.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1180-1183
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• 2002

Types of problems and solutions to vehicle routing problems are discussed. A case study on a public transport is conducted to discover the characteristics of problems in route selection. The characteristics of problems solved by certain technique or algorithm are also studied to investigate the capability of current techniques in solving public bus routing.

• IE interfaces
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• v.17 no.spc
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• pp.28-36
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• 2004

The main purpose of this study is to find out the optimal solution of the vehicle routing problem considering heterogeneous vehicle(s), double-trips, and multi depots. This study suggests a mathematical programming model with new numerical formula which considers the amount of delivery and sub-tour elimination and gives optimal solution by using OPL-STUDIO(ILOG). This study also suggests modified genetic algorithm which considers the improvement of the creation method for initial solution, application of demanding point, individual and last learning method in order to find excellent solution, survival probability of infeasible solution for allowance, and floating mutation rate for escaping from local solution. The suggested modified genetic algorithm is compared with optimal solution of the existing problems. We found the better solution rather than the existing genetic algorithm. The suggested modified genetic algorithm is tested by Eilon and Fisher data(Eilon 22, Eilon 23, Eilon 30, Eilon 33, and Fisher 10), respectively.

• 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.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.2
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• pp.91-97
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• 2006

The vehicle routing problem with time windows (VRPTW) is an important problem in third party logistics and supply chain management. We extend the VRPTW to the VRPTW with overtime and outsourcing vehicles (VRPTWOV) which allows the overtime of drivers and the possibility of using outsourcing vehicles. This problem can be applied to third party logistics companies for managing central distributor-local distributors, local distributor-retailers (or customers), and a manufacturer. We develop a mixed integer programming model and a genetic algorithm. Computational results demonstrate the efficiency of the developed genetic algorithm. We also develop a decision support system based on this genetic algorithm.