• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.207-213
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• 2021

Networks in Mobile ad hoc contain distribution and do not have a predefined structure which practically means that network modes can play the role of being clients or servers. The routing protocols used in mobile Ad-hoc networks (MANETs) are characterized by limited bandwidth, mobility, limited power supply, and routing protocols. Hybrid routing protocols solve the delay problem of reactive routing protocols and the routing overhead of proactive routing protocols. The Ant Colony Optimization (ACO) algorithm is used to solve other real-life problems such as the travelling salesman problem, capacity planning, and the vehicle routing challenge. Bio-inspired methods have probed lethal in helping to solve the problem domains in these networks. Hybrid routing protocols combine the distance vector routing protocol (DVRP) and the link-state routing protocol (LSRP) to solve the routing problem.

• Magazine of the Korean Society of Agricultural Engineers
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• v.6 no.1
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• pp.721-736
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• 1964

Flood routing is one of the most important engineering problems for the design of a spillway, and the procedures for the routing should be thoroughly understood by the engineers engaged in the planning of a spillway. There are many methods for the flood routing such as Muskingum, Steinberg, Puis, Holton, Goodrich, Rutter, Graves, Snyder, etc., which are being used in many countries. This article introduces the theory of the modified PuIs Method in detail which is exclusively being used in the Bureau of Reclamation, Department of Interior, U.S.A. Also, this article includes a routing example worked by the writter for the Ee-dong Reservoir of the Ki-ho Irrigation Association. in Kyong-gi Province.

• Korean Management Science Review
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• v.26 no.1
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• pp.171-182
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• 2009

We consider the inventory replenishment problem and the vehicle routing problem simultaneously in the vending machine operation. This problem is known as the inventory routing problem. We design a memory cell in the clonal selection algorithm. The memory cell store the best solution of previous solved problem and use an initial solution for next problem. In general, the other clonal selection algorithm used memory cell for reserving the best solution in current problem. Experiments are performed for testing efficiency of the memory cell in demand uncertainty. Experiment result shows that the solution quality of our algorithm is similar to general clonal selection algorithm and the calculations time is reduced by 20% when the demand uncertainty is less than 30%.

• Korean Management Science Review
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• v.21 no.3
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• pp.101-113
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• 2004

In the rapidly propagating Internet based electronic transaction environment. the importance of real time order confirmation has been more emphasized, In this paper, using data mining techniques, we develop intelligent operations decision model to allow real time order confirmation at the time the customer places an order with required delivery terms. Among various operation plannings used for order fulfillment. mill routing is the first interface decision point to link the order receiving at the marketing with the production planning for order fulfillment. Though linear programming based mathematical optimization techniques are mostly used for mill routing problems, some early orders should wait until sufficient orders are gathered for optimization. And that could effect longer order fulfillment lead-time, and prevent instant order confirmation of delivery terms. To cope with this problem, we provide the intelligent decision model to allow instant order based mill routing decisions. Data mining techniques of decision trees and neural networks. which are more popular in marketing and financial applications, are used to develop the model. Through diverse computational trials with the industrial data from the steel company. we have reported that the performance of the proposed approach is effective compared to the present heuristic only mill routing results. Various issues of data mining techniques application to the mill routing problems having linear programming characteristics are also discussed.

• IE interfaces
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• v.16 no.3
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• pp.280-290
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• 2003

Many firms are trying to optimize their production and distribution functions separately, but possible savings by this approach may be limited. Nowadays, it is more important to analyze these two functions simultaneously by trading off the costs associated with the whole. In this paper, I treat a production and distribution planning problem for single-period inventory products comprised of a single production facility and multiple customers, with the aim of optimally coordinating important and interrelated decisions of production sequencing and vehicle routing. Then, I propose a hybrid genetic algorithm incorporating several local optimization techniques, HGAP, for integrated production-distribution planning. Computational results on test problems show that HGAP is effective and generates substantial cost savings over Hurter and Buer's decoupled planning approach in which vehicle routing is first developed and a production sequence is consequently derived. Especially, HGAP performs better on the problems where customers are dispersed with multi-item demand than on the problems where customers are divided into several zones based on single-item demand.

• 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.

• IE interfaces
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• v.7 no.2
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• pp.87-97
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• 1994

Many vehicle routing methods have been suggested, which minimize the routing distances of vehicles to reduce the total transportation cost. But the more considerations the method takes, the higher complexites are involved in a large number of practical situations. The purpose of this paper is to develop a vehicle distribution planning system using heuristic algorithms and simulation techniques for home electronics companies. The vehicle distribution planning system developed by this study involves such complicated and stochastic conditions as one depot, multiple nodes(demand points), multiple vehicle types, multiple order items, and other many restrictions for operating vehicles. The proposed system is compared with the nearest neighbor method of the current system in terms of total logistics cost and driving time. This heuristics algorithm and simulation based distribution planning system is efficient in computational complexity, and give improved solutions with respect to the cost as well as the time. This method constructs a route with a minimum number of vehicles for a given demand.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.2
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• pp.102-113
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• 2004

This paper addresses the transportation planning that is based on genetic algorithm for determining transportation time and transportation amount of minimizing cost of distribution system. The vehicle routing of minimizing the transportation distance of vehicle is determined. A distribution system is consisted of a distribution center and many retailers. The model is assumed that the time horizon is discrete and finite, and the demand of retailers is dynamic and deterministic. Products are transported from distribution center to retailers according to transportation planning. Cost factors are the transportation cost and the inventory cost, which transportation cost is proportional to transportation distance of vehicle when products are transported from distribution center to retailers, and inventory cost is proportional to inventory amounts of retailers. Transportation time to retailers is represented as a genetic string. The encoding of the solutions into binary strings is presented, as well as the genetic operators used by the algorithm. A mathematical model is developed. Genetic algorithm procedure is suggested, and a illustrative example is shown to explain the procedure.

• Journal of the military operations research society of Korea
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• v.22 no.2
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• pp.182-199
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• 1996

Many vehicle routing methods have been suggested, which minimize the routing distances of vehicles to reduce the total transportation cost. But the more considerations the method takes, the higher complexites are involved in a large number of practical situations. The purpose of this paper is to develop a vehicle distribution planning system using heuristic algorithms and simulation techniques for home electronics companies. The vehicle distribution planning system developed by this study involve so complicated and stochastic conditions such as one depot, multiple nodes(demand points), multiple vehicle types, multiple order items, and other many restrictions for operating vehicles. The proposed system is compared with the nearest neighbor method and the savings method in terms of total logistics cost and driving time. This heuristic algorithm and simulation based distribution planning system is efficient in computational complexity, and give improved solutions with respect to the cost as well as the time. This method constructs a route with a minimum number of vehicles for a given demand.

• Journal of Korean Institute of Industrial Engineers
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• v.20 no.2
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• pp.19-30
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• 1994

Generally, a planning problem in a flexible manufacturing system is considered to be a composite of three interdependent tasks : part selection, loading, and routing mix. This research presents a mathematical model which can concurrently solve part selection, loading, and routing mix problems, so the problems that are caused by treating the planning problems independently are solved. The mathematical model is aimed to minimize system unbalance and the number of late parts, including constraints such as machine capacity, tool magazine capacity, and tool inventory. To illustrate the application of the model, an example is included. Solution procedure based on Lagrangian relaxation is also suggested for larger-sized problems.