• 산업경영시스템학회지
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• 제29권3호
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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.

• 산업경영시스템학회지
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• 제22권53호
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• pp.37-44
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• 1999

The problem to be studied here is the minimization of the total travel distance and the number of vehicles used for delivering goods to customers. Vehicle routes must also satisfy a variety of constraints such as fixed vehicle capacity, allowed operating time. Genetic algorithm to solve the VRPTW with heterogeneous fleet is presented. The chromosome of the proposed GA in this study has the 3-dimension. We propose GA that has the cubic-chromosome for VRPTW with heterogeneous fleet. The newly suggested ‘Cubic-GA (or 3-D GA)’ in this paper means the 2-D GA with GLS(Genetic Local Search) algorithms and is quite flexible. To evaluate the performance of the algorithm, we apply it to the Solomon's VRPTW instances. It produces a set of good routes and the reasonable number of vehicles.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2006년도 춘계공동학술대회 논문집
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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.

• 산업공학
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• 제17권spc호
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• pp.103-110
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• 2004

This paper presents a two-phase method for the vehicle routing problems with time windows(VRPTW). In a supply chain management(SCM) environment, timely distribution is very important problem faced by most industries. The VRPTW is associated with SCM for each customer to be constrained the time of service. In the VRPTW, the objective is to design the least total travel time routes for a fleet of identical capacitated vehicles to service geographically scattered customers with pre-specified service time windows. The proposed approach is based on ant colony optimization(ACO) and improvement heuristic. In the first phase, an insertion based ACO is introduced for the route construction and its solutions is improved by an iterative random local search in the second phase. Experimental results show that the proposed two-phase method obtains very good solutions with respect to total travel time minimization.

• 대한산업공학회지
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• 제32권2호
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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.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1993년도 춘계공동학술대회 발표논문 및 초록집; 계명대학교, 대구; 30 Apr.-1 May 1993
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• pp.354-366
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• 1993

In this paper, new algorithms for solving the multiple traveling salesman problem with time windows are presented. These algorithms are based on the flow based algorithms for solving the vehicle scheduling problem. Computational results on problems up to 750 customers indicate that these algorithms produce superior results to existing heuristic algorithms for solving the vehicle routing problems when the time windows are 'tight enough' where 'tight enough' is based on a metric proposed by desrosiers et al.(1987).

• 산업경영시스템학회지
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• 제29권4호
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• pp.75-82
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• 2006

The main objective of this study is to find out the shortest path of the vehicle routing problem with time window constraints by using both genetic algorithm and heuristic. Hard time constraints were considered to the vehicle routing problem in this suggested algorithm. Four different heuristic rules, modification process for initial and infeasible solution, 2-opt process, and lag exchange process, were applied to the genetic algorithm in order to both minimize the total distance and improve the loading rate at the same time. This genetic algorithm is compared with the results of existing problems suggested by Solomon. We found better solutions concerning vehicle loading rate and number of vehicles in R-type Solomon's examples R103 and R106.

• 대한산업공학회지
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• 제30권4호
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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.

• 한국컴퓨터정보학회논문지
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• 제24권1호
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• pp.167-178
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• 2019

In this paper, we study the multi-objectives vehicle and drone routing problem with time windows, MOVDRPTW for short, which is defined in an urban delivery network. We consider the dual modal delivery system consisting of drones and vehicles. Drones are used as a complement to the vehicle and operate in a point to point manner between the depot and the customer. Customers make various requests. They prefer to receive delivery services within the predetermined time range and some customers require fast delivery. The purpose of this paper is to investigate the effectiveness of the delivery strategy of using drones and vehicles together with a multi-objective measures. As experiment datasets, we use the instances generated based on actual courier delivery data. We propose a hybrid multi-objective evolutionary algorithm for solving MOVDRPTW. Our results confirm that the vehicle-drone mixed strategy has 30% cost advantage over vehicle only strategy.

• 산업경영시스템학회지
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• 제35권1호
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• pp.140-147
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• 2012

Vehicle routing problem is one of the traveling salesman problems with various conditions such as vehicle capacity limits, delivery time windows, as well as time dependent speeds in metropolitan area. In this research hourly vehicle moving speeds information in a typical metropolitan area are analyzed to use the results in the design procedure of VRP heuristic. Quality initial vehicle routing solutions can be obtained with adaption of the analysed results of the time periods with no vehicle speed changes. This strategy makes complicated time dependent vehicle speed simple to solve. Time dependent vehicle speeds are too important to ignore to obtain optimum vehicle routing search for real life logistics systems.