• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.52-58
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• 2005

In this paper, we address a real-world periodic vehicle routing problem with time windows (PVRPTW). In addition to the general requirements of single-day vehicle routing problem, each stop has required number of visits within a cycle period in PVRPTW. Thus, we need to determine optimized days of visit for each stop with consideration of the cycle-period days together. The problem also requires consistent vehicle assignment to the stops. We developed a clustering based 3-phase approach for this problem: 1) stop-route assignment, 2) stop-day assignment, and 3) stop sequencing within a single-day route. Using the approach, we could reduce the number of routes and improve the routing efficiency for several real-world 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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1170-1177
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• 2006

We apply VRP(Vehicle Routing Problem) to sludge collection system in this study. Sewage stores of villages are located in each village around a multipurpose dam. Sludge which is produced in sewage store of village is transported from the sewage store of village to the sewage treatment plants by the special purpose vehicle such as the tank lorry. In this paper, we propose sludge collection strategies which allocate each sewage store of village to sewage treatment plants and decide the schedule of sludge collection in order to collect sludge efficiently. The strategies aim to decrease transportation cost with deciding proposed vehicle routing and scheduling the sludge collection. When we decide route of vehicles, we consider the collection time in sewage store of village, distance between sewage store of villages and vehicle information as average velocity of vehicle, operation time of vehicle driver. We also develop the SCMS(Sludge Collection Management System) based on windows system with real data which is used in certain circumstance. And we experiment to figure out vehicle route and transportation cost throughout changing input data.

• Advances in aircraft and spacecraft science
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• v.10 no.5
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• pp.393-418
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• 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.

• 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.30 no.4
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• pp.45-60
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• 2005

We consider a vehicle routing problem with time window and dock capacity constraints (VRPTD). In most traditional models of vehicle routing problems with time window (VRPTW), each customer must be assigned to only one vehicle route. However demand of a customer may exceed the capacity of one vehicle, hence at least two vehicles may need to visit the customer We assume that each customer has Its own dock capacity. Hence, the customer can be served by only a limited number of vehicles simultaneously. Given a depot, customers, their demands, their time windows and dock capacities, VRPTD is to get a set of feasible routes which pass the depot and some customers such that all demands of each customer are satisfied Since VRPTD is NP-hard, a meta-heuristic algorithm is developed. The algorithm consists of two Procedures : the route construction procedure and the route scheduling procedure. We tested the algorithm on a number of instances and computational results are reported.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.04a
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• pp.15-16
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• 1999

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.1
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• pp.105-114
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• 2007

In this paper, we propose sludge collection strategies which allocate each sewage store of village to sewage treatment plants and decide the schedule of sludge collection in order to collect sludge efficiently. The strategies aim to decrease transportation cost with deciding proposed vehicle routing and scheduling the sludge collection. When we decide route of vehicles, we consider the collection time in sewage store of village, distance between sewage store of villages and vehicle information as average velocity of vehicle, operation time of vehicle driver. We also develop the SCMS (Sludge Collection Management System) based on windows system with real data which is used in certain circumstance. And we experiment to figure out vehicle route and transportation cost throughout changing input data.

• The KIPS Transactions:PartB
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• v.17B no.5
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• pp.389-398
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• 2010

The Vehicle Routing and Scheduling Problem with Time Windows(VRSPTW) is to establish a delivery route of minimum cost satisfying the time constraints and capacity demands of many customers. The VRSPTW takes a long time to generate a solution because this is a NP-hard problem. To generate the nearest optimal solution within a reasonable time, we propose the heuristic by using an ACO(Ant Colony Optimization) with multi-cost functions. The multi-cost functions can generate a feasible initial-route by applying various weight values, such as distance, demand, angle and time window, to the cost factors when each ant evaluates the cost to move to the next customer node. Our experimental results show that our heuristic can generate the nearest optimal solution more efficiently than Solomon I1 heuristic or Hybrid heuristic applied by the opportunity time.

• IE interfaces
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• v.23 no.2
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• pp.139-146
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• 2010

In this paper, we present the study of a real passenger transportation system. Passenger transportation problem aims to transport passengers from bus stops to their destinations by a fleet of vehicles while satisfying various constraints such as vehicle capacity, maximum allowable riding time in a bus, and time windows at destinations. Our problem also has special issues such as mixed loading, consideration of afternoon problem together with morning problem, and transferring passengers between vehicles. Our solution approach consists of three serial procedures: bus route generation, bus scheduling, and post optimization. Efficient heuristic algorithms were developed and implemented for the procedures. The proposed solution approach has been successfully applied to several real world problem instances and could reduce about 10% to 15% of buses.