• Title/Summary/Keyword: Pickup and Delivery Problem with Time Windows

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동일경로 제약을 갖는 집배송 차량 경로 수립 문제의 최적화 해법 (An Optimization Algorithm for The Pickup and Delivery Problem With Time Windows)

  • 강자영;장희정;강장하;박성수
    • 대한산업공학회지
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    • 제33권1호
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    • pp.33-43
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    • 2007
  • The pickup and delivery problem with time windows generally involves the construction of optimal routeswhich satisfy a set of transportation requests under pairing, precedence, time window, vehicle capacity, andavailability constraints. In this paper, we added some constraints to the problem and adopted an objectivefunction based on number of used vehicles, total travel distance and total schedule duration to consider morerealistic problems. A branch and price algohthm for the problem is proposed and an enumeration method is usedfor the subproblems. The algorithm was tested on randomly generated instances and computational results werereported.

유비쿼터스 기반의 적하와 하역 배송경로문제: u-MDPDPTW (Vehicle Routing Based on Pickup and Delivery in a Ubiquitous Environment : u-MDPDPTW)

  • 장용식;이현정
    • 지능정보연구
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    • 제13권1호
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    • pp.49-58
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    • 2007
  • 공급망의 물류흐름을 최적화하기 위해 여러 차고지를 기점으로 차량들이 다수의 적하와 하역장소를 거쳐 차고지로 돌아오는 최적의 배송경로를 계획하는 기존의 최적화모형 연구는 정수계획법(IP)에 기반을 둔 MDPDPTW(Multi-Depot Pickup and Delivery Problem with Time Windows) 모형이 있다. 이에 관한 연구들은 차고지의 차량들을 대상으로만 배송경로를 계획하기 때문에 운행 중인 차량을 고려할 때보다 효과적인 배송경로계획에 한계가 있다. 본 연구는 효과적인 공급망관리를 위하여 여러 차고지의 차량은 물론, 유비쿼터스 환경에서 배송화물과 운행 중인 차량상황을 포함한 배송상황을 기반으로 최적의 배송경로를 계획하는 IP기반 최적화모형인 u-MDPDPTW 모형을 제안하는데 그 목적이 있다. 또한, 기존 MDPDPTW 모형과 본 연구의 u-MDPDPTW 모형의 비교실험을 통하여 u-MDPDPTW 모형의 효과와 유용성을 보인다.

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Map과 GPS 기반의 혼적을 고려한 물류할당 및 모니터링 시스템 (Logistics Allocation and Monitoring System based on Map and GPS Information)

  • 박철순;랄손 바즈라차리야
    • 산업경영시스템학회지
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    • 제41권4호
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    • pp.138-145
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    • 2018
  • In the field of optimization, many studies have been performed on various types of Vehicle Routing Problem (VRP) for a long time. A variety of models have been derived to extend the basic VRP model, to consider multiple truck terminal, multiple pickup and delivery, and time windows characteristics. A lot of research has been performed to find better solutions in a reasonable time for these models with heuristic approaches. In this paper, by considering realtime traffic characteristics in Map Navigation environment, we proposed a method to manage realistic optimal path allocation for the logistics trucks and cargoes, which are dispersed, in order to realize the realistic cargo mixing allowance and time constraint enforcement which were required as the most important points for an online logistics brokerage service company. Then we developed a prototype system that can support above functionality together with delivery status monitoring on Map Navigation environment. First, through Map Navigation system, we derived information such as navigation-based travel time required for logistics allocation scheduling based on multiple terminal multiple pickup and delivery models with time constraints. Especially, the travel time can be actually obtained by using the Map Navigation system by reflecting the road situation and traffic. Second, we made a mathematical model for optimal path allocation using the derived information, and solved it using an optimization solver. Third, we constructed the prototype system to provide the proposed method together with realtime logistics monitoring by arranging the allocation results in the Map Navigation environment.

Aircraft delivery vehicle with fuzzy time window for improving search algorithm

  • C.C. Hung;T. Nguyen;C.Y. Hsieh
    • Advances in aircraft and spacecraft science
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    • 제10권5호
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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.