• Journal of the military operations research society of Korea
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• v.12 no.2
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• pp.37-55
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• 1986

Vehicle fleet planning problem is generic name given to a whole class of practical decision making problems which find the vehicle routes and schedules to accomplish the reqired service to customers using vehicles. In this paper the various problems are classified into the three groups according to their characteristics: (1) vehicle routing problems, (2) vehicle scheduling problems, and (3) vehicle routing and scheduling problems. The State of the art of each group is described and the future research directions are presented.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.145-152
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• 2021

In the Recent times, various technological enhancements in the field of artificial intelligence and big data has been noticed. This advancement coupled with the evolution of the 5G communication and Internet of Things technologies, has helped in the development in the domain of smart mine construction. The development of unmanned vehicles with enhanced and smart scheduling system for open-pit mine transportation is one such much needed application. Traditional open-pit mining systems, which often cause vehicle delays and congestion, are controlled by human authority. The number of sensors has been used to operate unmanned cars in an open-pit mine. The sensors haves been used to prove the real-time data in large quantity. Using this data, we analyses and create an improved transportation scheduling mechanism so as to optimize the paths for the vehicles. Considering the huge amount the data received and aggregated through various sensors or sources like, the GPS data of the unmanned vehicle, the equipment information, an intelligent, and multi-target, open-pit mine unmanned vehicle schedules model was developed. It is also matched with real open-pit mine product to reduce transport costs, overall unmanned vehicle wait times and fluctuation in ore quality. To resolve the issue of scheduling the transportation, we prefer to use algorithms based on artificial intelligence. To improve the convergence, distribution, and diversity of the classic, rapidly non-dominated genetic trial algorithm, to solve limited high-dimensional multi-objective problems, we propose a decomposition-based restricted genetic algorithm for dominance (DBCDP-NSGA-II).

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

• Industrial Engineering and Management Systems
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• v.11 no.4
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• pp.310-330
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• 2012

Scheduling is an important tool for a manufacturing system, where it can have a major impact on the productivity of a production process. In manufacturing systems, the purpose of scheduling is to minimize the production time and costs, by assigning a production facility when to make, with which staff, and on which equipment. Production scheduling aims to maximize the efficiency of the operation and reduce the costs. In order to find an optimal solution to manufacturing scheduling problems, it attempts to solve complex combinatorial optimization problems. Unfortunately, most of them fall into the class of NP-hard combinatorial problems. Genetic algorithm (GA) is one of the generic population-based metaheuristic optimization algorithms and the best one for finding a satisfactory solution in an acceptable time for the NP-hard scheduling problems. GA is the most popular type of evolutionary algorithm. In this survey paper, we address firstly multiobjective hybrid GA combined with adaptive fuzzy logic controller which gives fitness assignment mechanism and performance measures for solving multiple objective optimization problems, and four crucial issues in the manufacturing scheduling including a mathematical model, GA-based solution method and case study in flexible job-shop scheduling problem (fJSP), automatic guided vehicle (AGV) dispatching models in flexible manufacturing system (FMS) combined with priority-based GA, recent advanced planning and scheduling (APS) models and integrated systems for manufacturing.

• 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.

• Journal of Intelligence and Information Systems
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• v.15 no.3
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• pp.137-150
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• 2009

This paper proposes the hybrid heuristic method to apply the opportunity time to solve the vehicle routing and scheduling problem with time constraints(VRSPTW). The opportunity time indicates the idle time which remains after the vehicle performs the unloading service required by each customer's node. In this proposed heuristic, we add the constraints to VRSPTW model for the opportunity time. We also obtain the initial solution by applying the cost evaluation function to the insertion strategy considering the opportunity time. In addition, we improve the former result by applying the opportunity time to the tabu search strategy by swapping the customer's node. Finally, we suggest the construction strategies of initial routing which can efficiently acquire the nearest optimal solution from various types of data in terms of geographical condition, scheduling horizon and vehicle capacity. Our experiment show that our heuristic can get the nearest optimal solution more efficiently than the Solomon's I1 heuristic.

• 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.

• Journal of the military operations research society of Korea
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• v.26 no.1
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• pp.89-99
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• 2000

This paper deals with a heuristic algorithm for the vehicle routing-scheduling problem to minimize the total travel distance and the total cost. Because the aim of the Clarke-Wright method, one of famous heuristic methods, is to minimize the total travel distance of vehicles, it cannot consider the cost if the cost and the travel distance is not proportional. In the Clarke-Wright method, the route of each vehicle is found by using the saving matrix which is made by an assumption that the vehicle comes back to the starting point. The problem dealt with in the paper, however, does not need the vehicle to come back because each vehicle has its hoping-start-points and hoping-destination-points. Therefore we need a different saving matrix appropriate to this occasion. We propose a method to find an initial solution by applying network simplex method after transforming the vehicle routing-scheduling problem into the minimum cost problem. Moreover, we propose a method to minimize the total travel distance by using the modified saving matrix which is appropriate to no-return occasion and the method for the case of plural types of vehicles and freights.

• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.2
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• pp.39-47
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• 2010

As vehicles become intelligent for convenience and safety of drivers, in-vehicle networking (IVN) systems are essential components of intelligent vehicles. Recently, the chassis networking system which require increased network capacity and real-time capability is being developed to expand the application area of IVN systems. Also, FlexRay has been developed for the chassis networking system. However, FlexRay needs a complex scheduling method of static segment, which is a barrier for implementing the chassis networking system. Especially, if we want to migrate from CAN network to FlexRay network using CAN message database that was well constructed for the chassis networking system by automotive vendors, a novel scheduling method is necessary to be able to reduce design complexity. This paper presents a node-based scheduling method for FlexRay network system. And, in order to demonstrate the method's feasibility, its performance is evaluated through an experimental testbed.

• Proceedings of the Korean DIstribution Association Conference
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• 2003.05a
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• pp.55-70
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• 2003

The most transport companies are placing increasing emphasis on powerful new techniques for planning their vehicle operations. They have tried to improve their vehicle control and customer service capability by adopting tile advanced information technology, such as GPS(Global Position System) and Using Digital Map. But researches on the VRSP(vehicle routing St schedule problem) in this situation were very few. The purpose of this research is to develop vehicle scheduling heuristics for making a real-time dynamic VRSP under the situation that GPS and using Digital Map are equipped to the transport company. Modified savings techniques are suggested for the heuristic method and an insertion technique is suggested for the dynamic VRSP. The urgent vehicle schedule is based on the regular vehicle schedule. This study suggest on VRSP system using GPS and Digital Map and the performance of the suggested heuristics is illustrated through an real case example.