• Journal of the Korean Operations Research and Management Science Society
• /
• v.9 no.2
• /
• pp.3-8
• /
• 1984

This paper considers the intermediate warehouse location problem in a two stage distribution system where commodities are delivered from the given set of capacitated factories to customers via uncapacitated intermediate warehouses. In order to determine the subset of warehouses to open which minimizes the total distribution costs including the fixed costs associated with opening warehouses, the cross decomposition method for mixed integer programming recently developed by T.J. Van Roy is used. The cross decomposition unifies Benders decomposition and Lagrangean relaxation into a single framework that involves successive solutions to a primal subproblem and a dual subproblem. In our problem model, primal subproblem turns out to be a transshipment problem and dual subproblem turns out to be an intermediate warehouse location problem with uncapacitated factories.

• Management Science and Financial Engineering
• /
• v.9 no.1
• /
• pp.29-49
• /
• 2003

This paper develops channel reallocation methodologies for survival transmission networks, Any failure on a high-speed telecommunication network needs to be restored rapidly and a channel real-location methodology has an important role for the fast restoration. This paper considers the channel reallocation problems under a line restoration with distributed control, where the line restoration restores the failed channels by rerouting the channels along the two alternative routes. The objective is to determine the optimal number of rerouting channels on the alternative rerouting paths of a given transmission network, where the optimality criteria are the first, the last and the mean restoration times. For each criterion, the problem is formulated as a mixed integer programming and the optimal channel reallocation algorithm is suggested based upon the characterization of the optimal solution.

• Korean Management Science Review
• /
• v.10 no.1
• /
• pp.193-205
• /
• 1993

This paper presents a mathematical model for a class of vertical integration decisions. The problem structure of interest consists of raw material vendors, components suppliers, components processing plants, final product (assembly) plants and external components buyers. Economic feasibility of operating components plants instead of keeping outside suppliers is our major concern. The model also determines assignment of product lines and production volumes to each open plant considering the cost impacts of economies of scale and plant complexity. The problem formulation leads to a concave, mixed integer mathematical program. Given the state of the art of nonlinear programming techniques, it is often not possible to find global optima for reasonably sized such problems. We developed an optimization solution algorithm within the framework of Benders decomposition for the case of a piecewise linear concave cost function. It is shown that our algorithm generates optimal solutions efficiently.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.25 no.2
• /
• pp.87-100
• /
• 2000

As a result of rapid advances in communication technology, fiber optics have begun to be adopted in most telecommunication systems 3s an economic choice Due to the trend of evolution toward broadband communication network with fiber optics and electronic devices. the network design problem for broadband communication has been received a great deal of research attention recently. In this paper, we address a topological design problem for broadband local access network with uncertain demands, which has received surprisingly little attention so far. in our problem, we select a set of hubs and links for constructing network expected penalty cost for the amount of undersupplied In addition to the usual cost terms of the fixed demand problem Our problem can be approximated as a mixed 0-1 integer programming problem by using Szwarc’s linear approximation technique. Then the problem is transformed successfully into a version of classical network design model. Some computational experiments for the model and concluding remarks are described.

• Korean Management Science Review
• /
• v.21 no.2
• /
• pp.15-25
• /
• 2004

Great effort has been exerted to redesign the supply chain network as a means to improve corporate competitiveness. In this study, we present a mathematical model and a solution system to help redesign corporate logistics networks. The objective of the model is to minimize total logistics costs. We applied the solution system to real problem cases. We use the model and the concept to develop decision support system that is based on C++ with the use of CPLEX callable library as a solution engine. We tested and verified the DSS for redesigning the network of a large Korean electronics company. Through various scenario analyses. we recommend to redesign their supply chain network that demonstrates the possibility of substantial logistics cost savings.

• Korean Management Science Review
• /
• v.24 no.2
• /
• pp.43-56
• /
• 2007

VRP(Vehicle Routing Problem) is studied in this paper, where two different kinds of missions are to be completed. The objective is to minimize the total vehicle operating distance. A mixed integer programming formulation and a heuristic algorithm for a practical use are suggested. A heuristic algorithm consists of three phases such as clustering, constructing routes, and adjustment. In the first phase, customers are clustered so that the supply nodes are grouped with demand nodes to be served by the same vehicle. Vehicle routes are generated within the cluster in the second phase. Clusters and routes are adjusted in the third phase using the UF (unfitness) rule designed to determine the customers and the routes to be moved properly. It is shown that the suggested heuristic algorithm yields good performances within a relatively short computational time through computational experiment.

• Journal of the Korean Data and Information Science Society
• /
• v.21 no.2
• /
• pp.355-361
• /
• 2010

This paper addresses a mathematical approach to decision making in a real-world material distribution situation. The problem is characterized by a low-volume and highly-varied mix of products, therefore there is a lot of material movement between the facilities. This study focuses especially on the transportation scheduler with a tool that can be used to quantitatively analyze the volume of material moved, the type of truck to be used, production schedules, and due dates. In this research, we have developed a mixed integer programming problem using the minimum cost, multiperiod, multi-commodity network flow approach that minimizes the overall material movement costs. The results suggest that the optimization approach provides a set of feasible solution routes with the objective of reducing the overall fleet cost.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.59 no.3
• /
• pp.245-252
• /
• 2010

This paper proposes a constrained multi-area dispatch scheduling algorithm applicable to interconnected power system operations. The dispatch scheduling formulated as an MIP problem can be efficiently computed by GBD algorithm. GBD guarantees adequate computation speed and solution convergence by reducing the dimension of the dispatch scheduling problem. In addition, the regional decomposition technique based on ADM is introduced to obtain efficient inter-temporal OPF solution. It can find the most economic dispatch schedule incorporating power transactions without each regional utility's private information open.

• Journal of Korean Institute of Industrial Engineers
• /
• v.19 no.4
• /
• pp.125-135
• /
• 1993

An Unrelated Parallel Processing with Weighted jobs and Setup times scheduling prolem is studied. We consider a parallel processing in which a group of processors(machines) perform a single operation on jobs of a number of different job types. The processing time of each job depends on both the job and the machine, and each job has a weight. In addition each machine requires significant setup time between processing jobs of different job types. The performance measure is to minimize total weighted flow time in order to meet the job importance and to minimize in-process inventory. We present a 0-1 Mixed Integer Programming model as an optimizing algorithm. We also present a simple heuristic algorithm. Computational results for the optimal and the heuristic algorithm are reported and the results show that the simple heuristic is quite effective and efficient.

• Journal of Korean Institute of Industrial Engineers
• /
• v.22 no.3
• /
• pp.517-532
• /
• 1996

The area and time-dependent vehicle scheduling problem(ATVSP) is a generalization of the vehicle scheduling problem in which the travel speed between two locations depends on the passing areas and time of day. We propose a simple model for estimating area and time-dependent travel speeds in the ATVSP that relieves much burden for the data collection and storage problems. A mixed integer nonlinear programming formulation of the ATVSP is presented. We also propose three heuristics for the ATVSP, developed by extending and modifying existing heuristics for conventional vehicle scheduling problems. The results of computational experiments demonstrate that the proposed estimation model performs well and the saving method is the best among the three heuristics.