• Advances in aircraft and spacecraft science
• /
• 제10권5호
• /
• pp.393-418
• /
• 2023

Drones are increasingly used in logistics delivery due to their low cost, high-speed and straight-line flight. Considering the small cargo capacity, limited endurance and other factors, this paper optimized the pickup and delivery vehicle routing problem with time windows in the mode of "truck+drone". A mixed integer programming model with the objective of minimizing transportation cost was proposed and an improved adaptive large neighborhood search algorithm is designed to solve the problem. In this algorithm, the performance of the algorithm is improved by designing various efficient destroy operators and repair operators based on the characteristics of the model and introducing a simulated annealing strategy to avoid falling into local optimum solutions. The effectiveness of the model and the algorithm is verified through the numerical experiments, and the impact of the "truck+drone" on the route cost is analyzed, the result of this study provides a decision basis for the route planning of "truck+drone" mode delivery.

• 대한산업공학회지
• /
• 제33권2호
• /
• pp.265-272
• /
• 2007

The purpose of Vehicle Routing Problem (VRP) is to design the least costly (distance, time) routes for a fleet of identically capacitated vehicles to serve geographically scattered customers. There may be some restrictions such as the maximal capacity for each vehicle, maximal distance for each vehicle, time window to visit the specific customers, and so forth. This paper is concerned with VRP to minimize the sum of elapsed time from departure, where the elapsed time is defined as the time taken in a moving vehicle from the depot to each customer. It is important to control the time taken from departure in the delivery of perishable products or foods, whose freshness may deteriorate during the delivery time. An integer linear programming formulation is suggested and a heuristic for practical use is constructed. The heuristic is based on the set partitioning problem whose performances are compared with those of ILOG dispatcher. It is shown that the suggested heuristic gave good solutions within a short computation time by computational experiments.

• 한국항해항만학회:학술대회논문집
• /
• 한국항해항만학회 2009년도 공동학술대회
• /
• pp.149-150
• /
• 2009

The problem of vehicle routing problem(VRP) with pair operations of pick up and delivery are well-known in real applications in logistics networks, as in planning the routes for automatic guided vehicles(AGVs) in an automatic container terminal(ACT), warehouses or in some just-in-time services. This paper will present a formulation to modeling the problem mathematically which can be used to generate optimal routes of carried vehicles in the field to reduce the incurred cost of moving goods. This selected model could be used in (semi-)automatic short-term planning systems for vehicle fleet working in ACT, or in modern warehouses which the long list of requests is parted and sorted in preprocessing orders systems.

• 산업경영시스템학회지
• /
• 제29권3호
• /
• pp.62-69
• /
• 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.

• Management Science and Financial Engineering
• /
• 제18권1호
• /
• pp.27-37
• /
• 2012

This paper is motivated by a military cargo-plane routing problem which is a pickup-and-delivery problem in which load splits and node revisits are allowed (PDPLS). Although this recent evolution of a VRP-model enhances the efficiency of routing, a solution method is more of a challenge since the node revisits entail closed walks in modeling vehicle routes. For such a case, even a compact IP-formulation is not available and an effective method had been lacking until Nowak et al. (2008b) proposed a heuristic based on a tabu search. Their method provides very reasonable solu-tions as demonstrated by the experiments not only in their paper (Nowak et al., 2008b) but also in ours. However, the computation time seems intensive especially for the class of problems with dynamic transportation requests, including the military cargo-plane routing problem. This paper proposes a more scalable algorithm hybridizing a tabu search for pricing subproblem paused as a single-vehicle routing problem, with a column generation approach based on Dantzig-Wolfe decomposition. As tested on a wide variety of instances, our algorithm produces, in average, a solution of an equiva-lent quality in 10~20% of the computation time of the previous method.

• 대한안전경영과학회지
• /
• 제10권1호
• /
• pp.145-153
• /
• 2008

The vehicle routing problem determines each vehicle routes to find the transportation costs, subject to meeting the customer demands of all delivery points in geography. Vehicle routing problem 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. And computational experiments on these instances show that the proposed heuristic yields better results than the simple tabu search does.

• 한국경영과학회:학술대회논문집
• /
• 대한산업공학회/한국경영과학회 1992년도 춘계공동학술대회 발표논문 및 초록집; 울산대학교, 울산; 01월 02일 May 1992
• /
• pp.428-428
• /
• 1992

• 경영과학
• /
• 제24권2호
• /
• pp.43-56
• /
• 2007

VRP(Vehicle Routing Problem) is studied in this paper, where two different kinds of missions are to be completed. The objective is to minimize the total vehicle operating distance. A mixed integer programming formulation and a heuristic algorithm for a practical use are suggested. A heuristic algorithm consists of three phases such as clustering, constructing routes, and adjustment. In the first phase, customers are clustered so that the supply nodes are grouped with demand nodes to be served by the same vehicle. Vehicle routes are generated within the cluster in the second phase. Clusters and routes are adjusted in the third phase using the UF (unfitness) rule designed to determine the customers and the routes to be moved properly. It is shown that the suggested heuristic algorithm yields good performances within a relatively short computational time through computational experiment.

• 산업경영시스템학회지
• /
• 제44권2호
• /
• pp.36-42
• /
• 2021

This paper deals with a vehicle routing problem with resource repositioning (VRPRR) which is a variation of well-known vehicle routing problem with pickup and delivery (VRPPD). VRPRR in which static repositioning of public bikes is a representative case, can be defined as a multi-objective optimization problem aiming at minimizing both transportation cost and the amount of unmet demand. To obtain Pareto sets for the problem, famous multi-objective optimization algorithms such as Strength Pareto Evolutionary Algorithm 2 (SPEA2) can be applied. In addition, a linear combination of two objective functions with weights can be exploited to generate Pareto sets. By varying weight values in the combined single objective function, a set of solutions is created. Experiments accomplished with a standard benchmark problem sets show that Variable Neighborhood Search (VNS) applied to solve a number of single objective function outperforms SPEA2. All generated solutions from SPEA2 are completely dominated by a set of VNS solutions. It seems that local optimization technique inherent in VNS makes it possible to generate near optimal solutions for the single objective function. Also, it shows that trade-off between the number of solutions in Pareto set and the computation time should be considered to obtain good solutions effectively in case of linearly combined single objective function.

• 산업경영시스템학회지
• /
• 제33권4호
• /
• pp.201-208
• /
• 2010

This research is about developing an efficient solution procedure for the vehicle routing problem under varying vehicle moving speeds for hour-based time interval. Different moving speeds for every hour is too difficult condition to solve for this type of combinatorial optimization problem. A methodology to divide the 12 hour based time interval offered by government into 5 different time intervals and then divide delivery area into 12 small divisions first and then re-organizing them into 5 groups. Then vehicle moving speeds are no longer varying in each of the 5 divisions. Therefore, a typical TSP solution procedure may be applied to find the shortest path for all 5 divisions and then connect the local shortest paths to form a delivery path for whole area. Developed solution procedures are explained in detail with 60 points example.