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김우제,도승용,박순달,Katta G. Murty 한국로지스틱스학회 2001 로지스틱스연구 Vol.9 No.2
일일 간선수송문제는 각 화물터미널간에 수송물량이 주어진 상태에서 하루내에 수송하는 차량경로를 결정하는 문제이다. 소량화물을 가지는 일일 수송문제에 대해서는 각 화물터미널 간의 수송물량에 대해 중계지점을 통해 운송을 하는 수송체계가 유리하다. 본 연구에서는 이러한 수송체계를 효율적으로 구현하기 위한 유전알고리즘을 제시한다. 유전알고리즘에서는 중계지점을 선정하기 위한 유전알고리즘의 개체표현과 개체를 이용한 수송계획을 세우기 위해 절약개념을 이용한 휴리스틱 방법을 제시하였다. 그리고 유전알고리즘의 최적모수를 결정하기 위한 실험결과와 유전알고리즘의 해의 수렴을 검증하기 위한 실험결과가 제시되었다. Overnight linehaul scheduling is to determine the vehicle routing to move all freight from its originating terminal to its destination terminal after each shipment is picked up from the shipping dock. The transportation system to have several transshipment points is efficient for overnight linehaul scheduling with small amout shipment since each shipment may have a different transshipment point for overnight linehaul operations carrying small amount of shipment, The purpose of this paper is to present a genetic algorithm for the transportation system. It is suggested how to generate a chromosome for representing transshipment points and a heuristic for vehicle routing using the transshipment points. The computational results are resented for determining optimal parameters for the genetic algorithm, and showed the convergence of the genetic algorithm.
김우제,김종화,Murty, Katta G. 한국경영과학회 2000 한국경영과학회 학술대회논문집 Vol.- No.2
The chartered bus scheduling is to determine the allocation of buses to customer service requests. For the scheduling, we first represent the scheduling problem using a graph and develop a mathematical model. Second, we develop an algorithm for the scheduling problem including heuristic methods. We tested the performance of the algorithm on instances with real data. As a result, the total empty load driving time is reduced over 10% comparing with that of current practice at the company.
Applications of Clustering Models in Offshore Drilling for Crude Oil and Natural Gas
Hesham K. Alfares,Katta G. Murty,Ahmed A. AlSaaty 대한산업공학회 2019 Industrial Engineeering & Management Systems Vol.18 No.1
An important problem in offshore drilling for crude oil and natural gas is to find the optimum allocation of wells to drill, to multiple drilling rigs; to minimize the total cost of drilling. In practice, the drilling cost of each well is a function of both the distance to the drilling rig and the rig’s individual cost. In this paper, we consider this problem and present both an exact and a heuristic algorithm under two cases. Case 1 considers the problem in which rig locations are given, while Case 2 considers the problem in which rig locations are to be determined optimally. The new models and algorithms are unique because each drilling rig has a different cost rate per mile. Using data from an offshore oil field under development, the new models are used to minimize the total drilling cost for the two cases. In addition, a computational study is conducted, confirming the effectiveness of the proposed heuristic algorithm.