B. C. Cha

Changwon National University, Changnyeong, South Gyeongsang, South Korea

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Publications (8)7.58 Total impact

  • Source
    I.K. Moon, B.C. Cha, C.U. Lee
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    ABSTRACT: We have developed joint replenishment and consolidated freight delivery policies for a third party warehouse that handles multiple items, which have deterministic demand rates in a supply chain. Two policies are proposed and mathematical models are developed to obtain the optimal parameters for the proposed policies. Four efficient algorithms are presented to solve the mathematical models for the two policies. The performances of the two policies with the parameters obtained from the proposed algorithms are then compared with the common cycle approach for 1600 randomly generated problems. The results show the robust performance of the proposed algorithm for both policies.
    International Journal of Production Economics 01/2011; 133(1):344-350. · 2.08 Impact Factor
  • Source
    B.C. Cha, I.K. Moon, J.H. Park
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    ABSTRACT: We deal with the joint replenishment and delivery scheduling of the one-warehouse, n-retailer system in this paper. We suggest a more flexible policy for the joint replenishment and delivery scheduling of a warehouse compared with the existing researches. We introduce the mathematical model and two efficient algorithms for the joint replenishment and delivery scheduling of the warehouse. Subsequently, we develop the hybrid genetic algorithm (GA) and compare it with two efficient heuristic algorithms for extensive computational experiments. Further, we show the advantages of our GA in dealing easily with resource restrictions.
    Transportation Research Part E: Logistics and Transportation Review. 09/2008;
  • I. K. Moon, S. K. Goyal, B. C. Cha
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    ABSTRACT: In this article, we deal with the problem of determining the economic operating policy when a number of items are to be procured from a number of suppliers offering different quantity discounts schedules. In such inventory problems, a fixed cost is incurred with each replenishment order, independent of the suppliers as well as the items involved in the order. Further, the item involves a minor fixed cost. In such a system, it includes the supplier selection problem when considering the quantity discounts as well as the general joint replenishment problem. We develop a hybrid genetic algorithm for this NP-hard decision problem and extend it to systems with resource restrictions.
    Int. J. Systems Science. 01/2008; 39:629-637.
  • Source
    I K Moon, B C Cha, H C Bae
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    ABSTRACT: The concept of group technology has been successfully applied to many produc-tion systems, including flexible manufacturing systems. In this paper we apply group technology principles to the economic lot scheduling problem, which has been studied for over 40 years. We develop a heuristic algorithm and a hybrid genetic algorithm for the group technology economic lot scheduling problem. Numerical experiments show that the developed algorithms outperform the existing heuristics.
    International Journal of Production Research 12/2006; 44:4551-4568. · 1.46 Impact Factor
  • Source
    I.K. Moon, B.C. Cha
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    ABSTRACT: There are many resource restrictions in real production/inventory systems (for example, budget, storage, transportation capacity, etc.). But unlike other research areas, there is very little research to handle the joint replenishment problem (JRP) with resource restriction. The purpose of this paper is to develop two efficient algorithms for solving these problems. Firstly, we modify the existing RAND algorithm to be applicable to the JRP with resource restriction. Secondly, we develop a genetic algorithm for the JRP with resource restriction. Extensive computational experiments are performed to test the performances of the algorithms.
    European Journal of Operational Research 01/2006; · 2.04 Impact Factor
  • Source
    I. K. Moon, B. C. Cha
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    ABSTRACT: Optimal operating policy in most deterministic and stochastic inventory models is based on the unrealistic assumption that lead-time is a given parameter. In this article, we develop an inventory model where the replenishment lead-time is assumed to be dependent on the lot size and the production rate of the manufacturer. At the time of contract with a manufacturer, the retailer can negotiate the lead-time by considering the regular production rate of the manufacturer, who usually has the option of increasing his regular production rate up to the maximum (designed) production capacity. If the retailer intends to reduce the lead-time, he has to pay an additional cost to accomplish the increased production rate. Under the assumption that the stochastic demand during lead-time follows a Normal distribution, we study the lead-time reduction by changing the regular production rate of the manufacturer at the risk of paying additional cost. We provide a solution procedure to obtain the efficient ordering strategy of the developed model. Numerical examples are presented to illustrate the solution procedure.
    International Transactions in Operational Research 02/2005; 12(2):247 - 258. · 0.59 Impact Factor
  • Source
    B. C. Cha, I. K. Moon
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    ABSTRACT: In many practical situations quantity discounts on basic purchase price exist, and taking advantage of these can result in substantial savings. Quantity discounts have been considered in many production and inventory models. But unlike other research areas, there have been no studies to quantity discounts in the joint replenishment problem. The purpose of this paper is to develop efficient algorithms for solving this problem. Firstly, we suggest useful propositions to develop efficient heuristic algorithms. Secondly, we develop two algorithms using these propositions. Numerical examples are shown to illustrate the procedures of these algorithms. Extensive computational experiments are performed to analyze the effectiveness of the heuristics.
    Operations Research-Spektrum 01/2005; 27(4):569-581. · 1.41 Impact Factor
  • I. K. Moon, B. C. Cha, S. K. Kim

Publication Stats

62 Citations
7.58 Total Impact Points

Institutions

  • 2011
    • Changwon National University
      • Department of Business Administration
      Changnyeong, South Gyeongsang, South Korea
  • 2008
    • Electronics and Telecommunications Research Institute
      • Department of Postal and Logistics Technology Research
      Sŏul, Seoul, South Korea
  • 2005–2008
    • Pusan National University
      • Department of Industrial Engineering
      Pusan, Busan, South Korea