• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.595-598
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• 2002

This paper proposes neighborhood reduction techniques in local search of the customer decomposition subproblem in the Multi Depots Vehicle Routing Problem with Time Windows (MDVRPTW) by using geospatial relation among depots and customers. The neighborhood of the customer decomposition subproblem can be simply and well defined but it should include excessively bad solution candidates. Our techniques find such candidates by using information of the problem domain, geographical relation. We use our techniques in Tabu Search and evaluate the effectiveness in computer experiment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.294-303
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• 2023

During wartime, the operation of engineering equipment plays a pivotal role in bolstering the combat prowess of military units. To fully harness this combat potential, it is imperative to provide efficient support precisely when and where it is needed most. While previous research has predominantly focused on optimizing equipment combinations to expedite individual mission performance, our model considers routing challenges encompassing multiple missions and temporal constraints. We implement a comprehensive analysis of potential wartime missions and developed a routing model for the operation of engineering equipment that takes into account multiple missions and their respective time windows of required start and completion time. Our approach focused on two primary objectives: maximizing overall capability and minimizing mission duration, all while adhering to a diverse set of constraints, including mission requirements, equipment availability, geographical locations, and time constraints.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.2
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• pp.132-140
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• 2008

본 논문은 시간 제약을 갖는 차량 라우팅 문제를 해결하기 위해 유전자 알고리듬과 부분 최적화 알고리듬을 적용한 방법을 소개한다. 유전자 알고리듬에서의 염색체는 노드를 나타내는 정수의 순열로 표현되어 직접적인 해를 나타내지 않지만, 경험적 방법에 의한 해석을 통해 유효한 해로 변형되도록 하였다. 유전자 알고리듬에 의해 생성된 주어진 수의 우수한 해들에는 세 부분 최적화 방법이 순차적으로 적용되어 보다 좋은 해를 생성하도록 하였다. 부분 최적화 방법들에 의한 해는 다시 유전자 알고리듬의 해로 바뀌지 않도록 하여 두 알고리듬은 느슨하게 연결되도록 하였다. 솔로몬의 데이터를 이용한 실험에서 본 연구에서의 방법이 모든 문제에 대해 우수한 해를 생성함을 나타내었다. 특히, 지금까지 알려진 가장 우수한 경험적 방법에 비교될 만한 결과를 가져옴을 보였다.

• Journal of Intelligence and Information Systems
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• v.13 no.1
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• pp.49-58
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• 2007

MDPDPTW (Multi-Depot Pickup and Delivery Problem with Time Windows) is a typical model among the optimization models based on the pickup and delivery flow in supply chains. It is based on multi-vehicles in multi-depots and does not consider moving vehicles near pickup and delivery locations. In ubiquitous environments, it is possible to obtain information on moving vehicles and their baggage. Providing the proper context from the perspective of moving vehicles and their baggage allows for more effective vehicle routings. This study proposes Integer Programming-based MDPDPTW including the information on moving vehicles and their baggage in a ubiquitous environment: u-MDPDPTW, and shows the viability and effectiveness of u-MDPDPTW through comparative experiments of MDPDPTW and u-MDPDPTW.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.4
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• pp.382-389
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• 2011

Salesperson Monitoring System (SMS) is geographic based information system that supports business auditing, sales area coordinating and customer management for each salesperson. Conventional SMSs focus mainly on the monitoring or logging functions, i.e., a salesperson locating or moving trail tracking. However, the schedules have been planned by human planner, and they have rarely been managed with a software system like SMS. In this paper, a mixed integer programming model for a salesperson routing schedule is provided. Then, 2-phase Genetic Algorithm (GA) is proposed to make salesperson routing schedule. Experimental results show a validity of the proposed method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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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.