• Journal of the Korea Safety Management & Science
• /
• v.15 no.2
• /
• pp.193-204
• /
• 2013

The growing logistics strategy of a company is to optimize their vehicle route scheduling in their supply chain system. It is very important to analyze for continuous pickups and delivery vehicle scheduling. This paper is a computational study to investigate the effectiveness of continuous pickups and delivery vehicle routing problems. These scheduling problems have 3 subproblems; Inbound Vehicle Routing Problem with Makespan and Pickup, Line-haul Network Problem, and Outbound Vehicle Routing Problem with Delivery. In this paper, we propose 5 heuristic Algorithms; Selecting Routing Node, Routing Scheduling, Determining Vehicle Type with Number and Quantity, and Modification Selecting Routing Node. We apply these Algorithms to S vehicle company. The results of computational experiments demonstrate that proposed methods perform well and have better solutions than other methods considering the basic time and due-date.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.9
• /
• pp.143-153
• /
• 2021

In this paper, we propose "flexible routing with flex" to provide fast delivery by using the flexible routing for the delivery vehicle and crowd-shipper named flex. To this end, we have introduced an algorithm that can build the delivery plan for delivery vehicles and flexes. The introduced algorithm uses the 2-opt algorithm to construct routes with low complexity and acceptable quality, and the revised saving algorithm to assign customer orders to the flex. The algorithm allows the vehicle and the flex to function complement each other without separating the delivery vehicle from the flex. The experiments consider the 3 different instances named Random, Mixed, Cluster, and show that "the flexible routing with flex" has a better result than "vehicle only". The sensitivity analysis of the flex cost and time penalty shows "the flexible routing with flex" can provide better service not only to the customers who are serviced by flex but also to the customers who are serviced by the delivery vehicle.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.1
• /
• pp.167-178
• /
• 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.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.5 no.4
• /
• pp.243-253
• /
• 2010

Multihop data delivery in vehicular ad hoc networks (VANETs) suffers from the fact that vehicles are highly mobile and inter-vehicle links are frequently disconnected. In such networks, for efficient multihop routing of road safety information (e.g. road accident and emergency message) to the area of interest, reliable communication and fast delivery with minimum delay are mandatory. In this paper, we propose a multihop vehicle-to-infrastructure routing protocol named Vertex-Based Predictive Greedy Routing (VPGR), which predicts a sequence of valid vertices (or junctions) from a source vehicle to fixed infrastructure (or a roadside unit) in the area of interest and, then, forwards data to the fixed infrastructure through the sequence of vertices in urban environments. The well known predictive directional greedy routing mechanism is used for data forwarding phase in VPGR. The proposed VPGR leverages the geographic position, velocity, direction and acceleration of vehicles for both the calculation of a sequence of valid vertices and the predictive directional greedy routing. Simulation results show significant performance improvement compared to conventional routing protocols in terms of packet delivery ratio, end-to-end delay and routing overhead.

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

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

• IE interfaces
• /
• v.19 no.3
• /
• pp.202-213
• /
• 2006

In this paper, we develop a planning system for the routing and scheduling of vehicles in pickup and delivery service such as door-to-door parcel service. Efficient routing and scheduling of vehicles is very important in pickup and delivery service. The routing and scheduling problem is a variation of vehicle routing problem which has various realistic constraints. We develop a heuristic algorithm based on tabu search to solve the routing and scheduling problem. We develop a routing and scheduling system installed the algorithm as a planning engine. The system manage the basic data and uses GIS data to make a realistic route plan.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.36 no.3
• /
• pp.71-78
• /
• 2013

An efficient vehicle routing heuristic for different vehicle moving times for forward and backward between two points is studied in this research. Symmetric distance or moving times are assumed to move back and forth between two points in general, but it is not true in reality. Also, various moving speeds along time zones are considered such as the moving time differences between rush hours or not busy daytimes. To solve this type of extremely complicated combinatorial optimization problems, delivery zones are specified and delivery orders are determined for promising results on the first stage. Then delivery orders in each zone are determined to be connected with other zones for a tentative complete delivery route. Improvement steps are followed to get an effective delivery route for unsymmetric-time-varing vehicle moving speed problems. Performance evaluations are done to show the effectiveness of the suggested heuristic using computer programs specially designed and developed using C++.

• Journal of Korean Institute of Industrial Engineers
• /
• v.39 no.6
• /
• pp.554-561
• /
• 2013

As a special topic of the vehicle routing problems (VRP), VRPSDP extends the vehicle routing problem as considering simultaneous pickup and delivery for goods. The past studies have mainly dealt with a only weight constraint of a loading capacity for heterogeneous products. However. this study suggests VRPSDP considering separate loading area according to characteristics of loading species. The objective is to design a set of minimum distance routes for the vehicle routing assignment with independent capacity for heterogeneous species. And then we present a another HVRPSDP model which is easy to utilizes in a unique circumstance that is a guarantee of executing a task simultaneously from the various areas under restricted time and raising an application of vehicles that returns at the depot for the next mission like the military group. The optimal results of the suggested mathematical models are solved by the ILOG CPLEX software ver. 12.4 that is provided by IBM company.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.35 no.4
• /
• pp.171-178
• /
• 2012

A possible heuristic to solve metropolitan area vehicle routing problems with variable vehicle speeds is suggested in this research. Delivery hours are classified into 4 different time zones to make variable vehicle speeds no change within the same time zone to make TDVRP simple to solve. The suggested heuristic consists of 2 stages such as initial solution development step and initial solution improvement step. A computer program using C++ is constructed to evaluate the suggested heuristic. Randomly generated vehicle routing problems are used for the experiments. This heuristic could be helpful to logistics companies by increasing delivery efficiencies since the 4 zone classification is taken from the observed traffic information offered by a local government.