• Management Science and Financial Engineering
• /
• v.9 no.2
• /
• pp.47-68
• /
• 2003

We consider the customer order scheduling problem with job capacity restriction where the number of jobs in the shop at the same time is fixed. In the customer order scheduling problem, each job is part of some batch (customer order) and the composition of the jobs (product) in the batch is pre-specified. The objective function is associated with the completion time of the batches instead of the completion time of the jobs. We first summarize the known results for the general customer order scheduling problems. Then, we establish some new properties for the problems with job capacity restriction. For the case of unit processing time with the objective of minimizing makespan, we develop a polynomial-time optimal procedure for the two machine case. For the same problem with a variation of no batch alternation, we also develop a polynomial-time optimal procedure. Then, we show that the problems with the objectives of minimizing makespan and minimizing average batch completion time become NP-hard when there exist arbitrary number of machines. Finally, We propose optimal solution procedures for some special cases.

• Journal of environmental and Sanitary engineering
• /
• v.17 no.1
• /
• pp.28-35
• /
• 2002

A methods of minimizing the measurement error brought from gas compositions was proposed by Hot wire Anemometer which don't have measurement resistance to calculate of gas vent in sanitary landfill. It was determined measurement error to compared velocity at the center of pipe to calculate using rotor meter and density gas compositions with velocity at the center of pipe to calculate using water head indicator which don't have measurement resistance. Considering the methods of minimizing gas velocity in sanitary landfill using hot wire anemometer and rotor meter, it was found to minimize within 10% as error of gas vent in sanitary landfill.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.29 no.2
• /
• pp.45-57
• /
• 2004

The purpose of this paper is studying the valuation of option prices in Incomplete markets. A market is said to be incomplete if the given traded assets are insufficient to hedge a contingent claim. This situation occurs, for example, when the underlying stock process follows jump-diffusion processes. Due to the jump part, it is impossible to construct a hedging portfolio with stocks and riskless assets. Contrary to the case of a complete market in which only one equivalent martingale measure exists, there are infinite numbers of equivalent martingale measures in an incomplete market. Our research here is focusing on risk minimizing hedging strategy and its associated minimal martingale measure under the jump-diffusion processes. Based on this risk minimizing hedging strategy, we characterize the dynamics of a risky asset and derive the valuation formula for an option price. The main contribution of this paper is to obtain an analytical formula for a European option price under the jump-diffusion processes using the minimal martingale measure.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.20 no.4
• /
• pp.330-336
• /
• 2015

This paper presents a loss-minimizing vector control method for interior permanent magnet synchronous motor (IPMSM). Conventionally, maximum torque per ampere (MTPA) control, which minimizes copper loss, has been widely used in industry. Iron loss, however, is not considered in MTPA control. In this paper, the loss model, including iron loss and copper loss, is derived to further reduce drive loss. The loss-minimizing vector controller is implemented based on the loss model. The controller generates optimal current vectors according to the operating conditions. The performance and validity of the proposed method are proved by experimental results through comparison with conventional methods.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.49 no.2
• /
• pp.56-61
• /
• 2000

In the paper, the system loss sensitivity index that implies the incremental system loss with respect to the change of bus power is derived using optimization technique. The index λ reaches $\infty$ at critical loading point and can be applied to actual power systems for following purposes. 1) Evaluation of system voltage stability 2)Optimal investment of reactive power focused on minimizing system loss and maximizing system voltage stability 3)Optimal re-location of reactive power focused on minimizing system loss and maximizing system voltage stability 4)Optimal load shedding in case of severe system contingency focused on minimizing system loss and maximizing system voltage stability. Case studies for each application have proved their effectiveness.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.44 no.1
• /
• pp.21-24
• /
• 1995

The larger and the more complicated the system size and configuration grow, the more serious the system loss problem becomes. Exessive system loss causes severs system voltage depression, which even may result in system voltage collapse. This paper proposes an effective tool for minimizing the system power loss by optimal re-location of the static condenser based on the system loss sensitivity index .lambda.$_{Q}$. It is possible to determine the optimal location and amount of VAR investment for minimizing the system loss by priority of .lambda.$_{Q}$ index given for each bus. Several computational techniques for avoiding divergency of the load flow solution are proposed. The loss sensitivity index .lambda.$_{Q}$ uses information of normal power flow equations and their Jacobians. Two case studies proved the effectiveness of the algorithm proposed.posed.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.19 no.39
• /
• pp.275-284
• /
• 1996

It can be made a definition that scheduling is a imposition of machinery and equipment to perform a collection of tasks. Ultimately scheduling is an assessment of taking order for which would be perform. So it is called "sequencing" in other words. In a job shop scheduling, the main object is to making delivery in accordance with the due date and order form customer, not to producing lots of quantity with minimizing mean flow time in a given time. Actually, in a company, they concentrate more in the delivery than minimizing the mean flow time. Therefore this paper suggest a new priority dispatching rule under consideration as below in a n/m job shop scheduling problem with due date. 1. handling/transportation time, 2. the size of customer order With this algorithm, we can make a scheduling for minimizing the tardiness of delivery which satisfy a goal of production.roduction.

• Journal of Korean Society of Transportation
• /
• v.18 no.1
• /
• pp.87-97
• /
• 2000

Signal optimization model is divided bandwidth-maximizing model and delay-minimizing model. Bandwidth-maximizing model express model formulation as MILP(Mixed Integer Linear Programming) and delay-minimizing model like TRANSYT-7F use "hill climbing" a1gorithm to optimize signal times. This study Proposed optimization model using genetic algorithm one of evolution algorithm breaking from existing optimization model This Proposed model were tested by several scenarios and evaluated through NETSIM with TRANSYT-7F\`s outputs. The result showed capability that can obtain superior solution.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.13 no.2
• /
• pp.59-65
• /
• 1988

This paper discusses the problem of coordinating aggregate planning and production schedules, minimizing the combined set-up inventory and capacity costs. In this study, by using the relation of fixed production quantity and the number of set-up we develop a heuristirc procedure of solving the discrete demand, fixed production quantity, variable capacity problem. First, we obtain the trade-off between set-up cost and capacity cost, then search the point minimizing the combined inventory and capacity costs.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2001.10a
• /
• pp.269-272
• /
• 2001

In this paper, we presents a systematic methodology for minimizing tardiness and maximizing resource utilization in a multi-plant supply chain. A methodology is represented to a multi-objective mathematical program model. The model offers flexible and efficient multi-plant planning and scheduling. Also, We develope a realistic and flexible planning model using the genetic algorithm to solve the model.