• IE interfaces
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• 제17권spc호
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• pp.28-36
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• 2004

The main purpose of this study is to find out the optimal solution of the vehicle routing problem considering heterogeneous vehicle(s), double-trips, and multi depots. This study suggests a mathematical programming model with new numerical formula which considers the amount of delivery and sub-tour elimination and gives optimal solution by using OPL-STUDIO(ILOG). This study also suggests modified genetic algorithm which considers the improvement of the creation method for initial solution, application of demanding point, individual and last learning method in order to find excellent solution, survival probability of infeasible solution for allowance, and floating mutation rate for escaping from local solution. The suggested modified genetic algorithm is compared with optimal solution of the existing problems. We found the better solution rather than the existing genetic algorithm. The suggested modified genetic algorithm is tested by Eilon and Fisher data(Eilon 22, Eilon 23, Eilon 30, Eilon 33, and Fisher 10), respectively.

• Journal of Korean Society of Industrial and Systems Engineering
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• 제28권2호
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• pp.8-17
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• 2005

This paper dealt with a kind of heterogeneous vehicle routing problem with known demand and time deadline of customers. The customers are supposed to have one of tight deadline and loose deadline. The demand of customers with tight deadline must be fulfilled in the deadline. However, the late delivery is allowed to customers with loose deadline. That is, the paper suggests a model to minimize total acquisition cost, total travel distance and total violation time for a fleet size and mix vehicle routing problem with time deadline, and proposes a heuristic algorithm for the model. The proposed algorithm consists of two phases, i.e. generation of an initial solution and improvement of the current solution. An initial solution is generated based on a modified insertion heuristic and iterative Improvement procedure is accomplished using neighborhood generation methods such as swap and reallocation. The proposed algorithm is evaluated using a well known numerical example.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 대한산업공학회/한국경영과학회 2006년도 춘계공동학술대회 논문집
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• pp.1740-1745
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• 2006

This paper is concerned with a novel heuristic algorithm for the multi-trip vehicle routing problem with time windows. The objective function is the minimization of total vehicle operating time, fixed cost of vehicle and the minimization of total lateness of customer. A mixed integer programming formulation and a heuristic algorithm for a practical use are suggested. A heuristic algorithm is constructed two phases such as clustering and routing. Clustering is progressed in order to assign appropriate vehicle to customer, and then vehicle trip and route are decided considering traveling distance and time window. It is shown that the suggested heuristic algorithm gives good solutions within a short computation time by experimental result.

• Journal of Korean Society of Industrial and Systems Engineering
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• 제14권24호
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• pp.141-147
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• 1991

This paper presents extended model for the vehicle routing problem, which allows multiple visits to a node by multiple vehicles. Multiple visits enables us split delivery. After formulating this multiple visits model mathematically, a two stage heuristic algorithm is developed by decomposition approach. This model consists of two sub-problem. The one is fixed cost transportation problem and the other is transportation problem.

• International Journal of Computer Science & Network Security
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• 제21권1호
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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.

• Korean Management Science Review
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• 제30권2호
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• pp.31-42
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• 2013

The vehicle routing problem (VRP) can be described as a problem to find the optimum traveling routes from one or several depot (s) to number of geographically scattered customers. This study executes a revised Heterogeneous Vehicle Routing Problem (HVRP) to minimize the cost that needs to conduct efficiently the snow removal operations of Air Wing under available resources and limited operations time. For this HVRP, we model the algorithm of an hybrid Ant Colony System (ACS). In the initial step for finding a solution, the modeled algorithm applies various alterations of a parameter that presents an amount of pheromone coming out from ants. This improvement of the initial solution illustrates to affect to derive better result ultimately. The purpose of this study proves that the algorithm using Hybrid heuristic incorporated in tabu and ACS develops the early studies to search best solution.

• Industrial Engineering and Management Systems
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• 제12권2호
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• pp.161-170
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• 2013

Deployment of green transportation in reverse logistics is a key issue for low carbon technologies. To cope with such logistic innovation, this paper proposes a hybrid approach to solve practical vehicle routing problem (VRP) of pickup type that is common when considering the reverse logistics. Noticing that transportation cost depends not only on distance traveled but also on weight loaded, we propose a hierarchical procedure that can design an economically efficient reverse logistics network even when the scale of the problem becomes very large. Since environmental concerns are of growing importance in the reverse logistics field, we need to reveal some prospects that can reduce $CO_2$ emissions from the economically optimized VRP in the same framework. In order to cope with manifold circumstances, the above idea has been deployed by extending the Weber model to the generalized Weber model and to the case with an intermediate destination. Numerical experiments are carried out to validate the effectiveness of the proposed approach and to explore the prospects for future green reverse logistics.

• Journal of Intelligence and Information Systems
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• 제15권3호
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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 Institute of Industrial Engineers
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• 제33권4호
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• pp.469-479
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• 2007

This paper focuses on the capacitated vehicle routing problem that determines the routes of vehicles in such a way that each customer must be visited exactly once by one vehicle starting and terminating at the depot while the vehicle capacity and the travel time constraints must be satisfied. The objective is to minimize the total traveling cost. Due to the complexity of the problem, we suggest a tabu search algorithm that combines the features of the existing search heuristics. In particular, our algorithm incorporates the neighborhood reduction method using the proximity information of the Voronoi diagram corresponding to each problem instance. To show the performance of the Voronoi tabu search algorithm suggested in this paper, computational experiments are done on the benchmark problems and the test results are reported.

• Journal of Korean Society of Industrial and Systems Engineering
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• 제19권37호
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• pp.263-269
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• 1996

The cost and customer service level of a logistics system depend primarily on the system design of the physical supply system and physical distribution system. The study presents the mathematical model and a huristic solution method of a combined location - vehicle routing problem(LVRP). In LVRP the objective is to determine the number and location of the distribution centers, the allocation of customers to distribution centers, and the vehicle delivery routes, so as to minimize the logistics total cost and satisfy the customer.