Decomposition Model of Vehicle Routing Problem and Hybrid Approach Mixing Branch-and-bound Techniques and Meta-heuristics

Kazutoshi Sakakibara,Muneyoshi Iyama,Ikuko Nishikawa 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8

In this paper, we consider a class of pickup and delivery problems. The problem requires that any paired pickup and delivery locations have to be served by one vehicle and the pickup location has to be scheduled before the corresponding delivery location in the route. In order to find near-optimal transportation plans, we discuss a hybrid approach mixing branch-and bound techniques and meta-heuristics. The key idea is that an original problem is decomposed into a set of sub-problems, in which the number of customers assigned to each vehicle is fixed, and respective sub-problem is solved by meta-heuristics such as simulated annealing heuristics. Then, promising sub-problems are able to be found efficiently by using branch-and-bound techniques. The effectiveness and the potential of the proposed approach are evaluated by a series of computational experiments.

Autonomous Delivery Robot Operating System for 24-hour Delivery Service

Seu-jan Kim,Tai-Won Um 한국디지털콘텐츠학회 2023 The Journal of Contents Computing Vol.5 No.2

The demand for last-mile delivery is increasing due to the rise of ecommerce and urbanization trends, leading to various social problems. To address these problems, the introduction of autonomous delivery robots is being researched. However, most studies on delivery robots for the last mile sector assume customer attendance delivery, so it is essential to develop robots capable of door-to-door delivery. This paper proposes a 24-hour delivery operation system for urban environments. The system uses door-to-door delivery robots and applies a combinatorial optimization strategy based on deep reinforcement learning using algorithms such as STRUCT2VEC, LSTM and ATTENTION. This enables the system to solve routing problems effectively and in a short time to meet customer requirements.

시뮬레이션기반 분만간호 실습이 간호대학생의 문제해결의 적극성, 임상수행능력, 팀효능감에 미치는 효과

서은희 대한산업경영학회 2023 산업융합연구 Vol.21 No.8

The purpose of this study was to test the effects of simulation-based delivery nursing practice on proactivity of problem-solving, clinical Performance and team efficacy in nursing college students. This study conducted with a quasi-experimental one group pretest-posttest design. The subjects of the study were those who participated in the pretest-posttest survey among third graders in nursing who took a simulation-based delivery nursing practice class at S university in D city, and finally, data from 78 students who completed the survey were analyzed. Data collection was conducted from August 30, 2022 to October 28, 2022, and data were analyzed using SPSS 27.0 program. The findings suggest that simulation-based delivery nursing practice had a positive effect by significantly increasing on problem-solving proactivity, clinical performance ability, and team efficacy. However, There are limitations in generalizing the study results. therefore based on a sufficient number of samples, the effects should be verified through randomized controlled pre-and post-test and, To determine whether the effects are consistent, it will be necessary to follow up in the long term. 본 연구는 시뮬레이션기반 분만간호 실습이 간호대학생의 문제해결의 적극성, 임상수행능력, 팀효능감에 미치는 효과를 검증하기 위한 단일군 전·후 설계의 유사실험 연구이다. D시에 소재한 S대학의 간호대학생 3학년을 대상으로 시뮬레이션기반 분만간호 실습을 운영하였으며, 사전·사후 설문에 응답한 78명의 자료를 분석하였다. 자료수집은 2022년 8월 30일부터 2022년 10월 28일까지 이루어졌으며, 자료분석은 SPSS 27.0 프로그램을 사용하여 분석하였다. 연구 결과 시뮬레이션기반 분만간호 실습은 간호대학생의 문제해결의 적극성, 임상수행능력, 팀효능감에 긍정적인 효과가 있는 것으로 확인되었다. 이에 간호대학생에게 임상 현장 사례를 기반한 분만간호 시뮬레이션 교육을 적용한다면 임상에서 요구하는 핵심 능력 및 교육 만족도 향상에 긍정적인 영향을 미칠 것으로 생각된다. 그러나 연구결과를 일반화하는데 한계가 있어 충분한 표본 수의 무작위 대조군 사전·사후 연구를 통해 그 효과를 검증하고, 효과의 지속성을 장기적으로 추적 관찰할 필요가 있다.

Aircraft delivery vehicle with fuzzy time window for improving search algorithm

C.C. Hung,T. Nguyen,C.Y. Hsieh Techno-Press 2023 Advances in aircraft and spacecraft science Vol.10 No.5

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.

컨테이너 운송체계 개선을 위한 화물수거-배송계획 시스템 개발

윤항묵(Hang-Mook Yoon),황흥석(Heung-Suk Hwang),김형보(Hyung-Bo Kim) 한국항해항만학회 2005 한국항해항만학회지 Vol.29 No.3

본 연구는 화물 운송 문제에 GIS 기법을 응용하여 화물의 수거 및 배송문제를 개선한 논문이다. 최근 국내 물류업체들은 인터넷을 기반으로 주문, 검색 및 화물의 추적 등을 온라인상에서 실행토록 하는 방법을 중시하게 되었다. 국내외 배송 관련 기업들은 빠른 서비스를 요구하는 긴급주문의 비중이 커 가는 시장변환에 대처해서, 서비스 능력의 향상과 효율적인 차량관리를 위해서 GPS와 TRS 등의 정보통신기술을 이용하여, 기업의 배차업무를 개선하려고 노력하고 있다. 하지만 아직까지 배차 담당자의 의사결정을 지원할 수 있는 배차기법에 대한 연구는 거의 이루어 지지 않고 있는 것이 현 실정이다. 본 연구에서는 GIS기반 하에서의 거리산정방법을 제안하고 이를 이용하여 차량운송 및 수거계획 알고리즘을 개발하였다. 또한 본 연구에서는 차량 및 화물정보를 GIS환경에서 실시간으로 조회해 볼 수 있도록 하였으며, 입출력자료와 차량 및 화물정보 조회결과를 GIS환경에서 구현하도록 하였다. 사용자들을 위하여 GUI-type 프로그램을 개발하고 실 예제를 통하여 Sample 출력을 보였다. 본 연구의 결과는 추후 약간의 수정 보완을 통하여 실제 물류센터에서의 운송계획 작성시 바로 적용될 수 있을 것이라고 판단된다. This paper provides a method to implement IT system for supply chain management problem. The fundamental scheduling issues that arise in the pickup delivery system are optimizing the system with the minimum cost, the maximum throughput and the service level. This study is concerned with the development of the customer responsive pickup-delivery system based on e-logistics and demand chain management. Through this study, the pickup-delivery problem of the vehicle using the GIS PDP and GUIㆍtype computer programs are formulated. The computational results show that the proposed method is very effective on a set of test problems.

Persistent UAV delivery logistics: MILP formulation and efficient heuristic

Song, Byung Duk,Park, Kyungsu,Kim, Jonghoe Elsevier 2018 COMPUTERS & INDUSTRIAL ENGINEERING Vol.120 No.-

<P><B>Abstract</B></P> <P>The high efficiency, flexibility and low cost of Unmanned Aerial Vehicles (UAVs) present huge application opportunities in various industries. Among those various applications, we focus herein on the use of UAVs in delivery logistics. The UAV logistics system has some fundamental characteristics that distinguish it from the usual ground logistics such as limited flight time, loadable capacity, effect of cargo weight on flight ability, and others. To handle the above issues, we propose a Mixed Integer Linear Programming (MILP) formulation for derivation of persistent UAV delivery schedules. To address the computational issues, a Receding Horizon Task Assignment (RHTA) heuristic is developed and tested with numerical examples for island-area delivery.</P> <P><B>Highlights</B></P> <P> <UL> <LI> UAV delivery logistics with multiple recharge/reload stations was considered. </LI> <LI> UAVs visit station, refill consumables and return to service persistently. </LI> <LI> Amount of loaded product effects on the flight time of UAVs during delivery. </LI> <LI> Validity of the proposed model was demonstrated via island area delivery example. </LI> <LI> Performance of mathematical formulation and heuristic were tested and compared. </LI> </UL> </P>

A Hybrid Genetic Algorithm for the Location-Routing Problem with Simultaneous Pickup and Delivery

Ismail Karaoglan,Fulya Altiparmak 대한산업공학회 2011 Industrial Engineeering & Management Systems Vol.10 No.1

In this paper, we consider the Location-Routing Problem with simultaneous pickup and delivery (LRPSPD) which is a general case of the location-routing problem. The LRPSPD is defined as finding locations of the depots and designing vehicle routes in such a way that pickup and delivery demands of each customer must be performed with same vehicle and the overall cost is minimized. Since the LRPSPD is an NP-hard problem, we propose a hybrid heuristic approach based on genetic algorithms (GA) and simulated annealing (SA) to solve the problem. To evaluate the performance of the proposed approach, we conduct an experimental study and compare its results with those obtained by a branch-and-cut algorithm on a set of instances derived from the literature. Computational results indicate that the proposed hybrid algorithm is able to find optimal or very good quality solutions in a reasonable computation time.

A Hybrid Genetic Algorithm for the Location-Routing Problem with Simultaneous Pickup and Delivery

Karaoglan, Ismail,Altiparmak, Fulya Korean Institute of Industrial Engineers 2011 Industrial Engineeering & Management Systems Vol.10 No.1

In this paper, we consider the Location-Routing Problem with simultaneous pickup and delivery (LRPSPD) which is a general case of the location-routing problem. The LRPSPD is defined as finding locations of the depots and designing vehicle routes in such a way that pickup and delivery demands of each customer must be performed with same vehicle and the overall cost is minimized. Since the LRPSPD is an NP-hard problem, we propose a hybrid heuristic approach based on genetic algorithms (GA) and simulated annealing (SA) to solve the problem. To evaluate the performance of the proposed approach, we conduct an experimental study and compare its results with those obtained by a branch-and-cut algorithm on a set of instances derived from the literature. Computational results indicate that the proposed hybrid algorithm is able to find optimal or very good quality solutions in a reasonable computation time.

A Pickup and Delivery Problem Based on AVL and GIS

Hwang, Heung-Suk Korean Institute of Industrial Engineers 2003 Industrial Engineeering & Management Systems Vol.2 No.1

The fundamental design issues that arise in the pickup and delivery system planning are optimizing the system with minimum cost and maximum throughput and service level. This study is concerned with the development of pickup and delivery system with customer responsive service level, DCM(Demand Chain Management). The distribution process and service map are consisted of manufacturing, warehousing, and pickup and delivery. First we formulated the vehicle pickup and delivery problem using GIS-VRP method so as to satisfy the customer service requests. Second, we developed a GUI-type computer program using AVL, automated vehicle location system. The computational results show that the proposed method is very effective on a set of test problems.

Max–Min Fairness Approach for Collaborative Vehicle Routing Cost Allocation

Shunichi Ohmori,Kazuho Yoshimoto 대한산업공학회 2021 Industrial Engineeering & Management Systems Vol.20 No.3

We consider a collaborative vehicle-routing problem involving two or more companies jointly operating delivery fulfillment. It is known that the collaborative routing improves the delivery efficiency that results in a lower cost, CO₂ emission, and traffic congestions. However, cost allocation is a major challenge in the establishment of collaboration because each company has a set of customers whose locations and demands are different. In this paper, we propose an optimization-based framework for determining the optimal vehicle routing and cost allocation of companies in a collaboration, in an unbiased manner. The proposed method relies on max–min fairness that is a widely accepted concept. We formulated this problem as a multi-objective optimization problem. Thereafter, we reformulated the single-objective problem in which the fairness is considered by maximizing the minimum utility of each company in the collaboration. We quantify the utility by applying a fuzzy membership function based on the gained cost benefit. We present computational results ranging from 10 to 80 customers. In all cases, significant improvements are observed in the cost-benefit balance each company gains over the one obtained through the methods compared.