• Journal of Electrical Engineering and Technology
• /
• v.6 no.1
• /
• pp.32-41
• /
• 2011

This paper presents a new method of Fuzzy Particle Swarm Optimization (FPSO)-based Congestion Management (CM) by optimal rescheduling of active powers of generators. In the proposed method, generators are selected based on their sensitivity to the congested line for efficient utilization. The task of optimally rescheduling the active powers of the participating generators to reduce congestion in the transmission line is attempted by FPSO, Fitness Distance Ratio PSO (FDR-PSO), and conventional PSO. The FPSO and FDR-PSO algorithms are tested on the IEEE 30-bus and Practical Indian 75-bus systems, after which the results are compared with conventional PSO to determine the effectiveness of CM. Compared with FDR-PSO and PSO, FPSO can better perform the optimal rescheduling of generators to relieve congestion in the transmission line.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.29 no.3
• /
• pp.111-127
• /
• 2004

We consider a supply chain model with a make-to-order production facility and a single supplier. The model we treat here is a special case of a two-echelon inventory model. Unlike classical two-echelon systems, the demand process at the supplier is affected by production process at the production facility as well as customer order arrival process. In this paper, we address that how the demand variability impacts on the optimal replenishment policy. To this end, we incorporate Erlang and phase-type demand distributions into the model. Formulating the model as a Markov decision problem, we investigate the structure of the optimal replenishment policy. We also implement a sensitivity analysis on the optimal policy and establish its monotonicity with respect to system cost parameters.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.53 no.3
• /
• pp.187-197
• /
• 2004

This paper presents a window-based load management system (LMS) developed as a decision-making tool in the competitive electricity market The developed LMS can help the users to monitor system load patterns, analyze their past energy consumption and schedule for the future energy consumption. The LMS can also provide the effective information on real-time energy/cost monitoring, consumed energy/cost analysis, demand schedule and cost-savings. Therefore. this LMS can be used to plan the optimal demand schedule and consumption strategy.

• Management Science and Financial Engineering
• /
• v.18 no.1
• /
• pp.13-20
• /
• 2012

This paper considers a revenue maximization problem on a single processor. Each job is identified as its processing time, initial reward, reward decreasing rate, and preferred start time. If the processor starts a job at time zero, revenue of the job is its initial reward. However, the revenue decreases linearly with the reward decreasing rate according to its processing start time till its preferred start time and finally its revenue is zero if it is started the processing after the preferred time. Our objective is to find the optimal sequence which maximizes the total revenue. For the problem, we characterize the optimal solution properties and prove the NP-hardness. Based upon the characterization, we develop a branch-and-bound algorithm for the optimal sequence and suggest five heuristic algorithms for efficient solutions. The numerical tests show that the characterized properties are useful for effective and efficient algorithms.

• Management Science and Financial Engineering
• /
• v.15 no.1
• /
• pp.33-49
• /
• 2009

We examine the effectiveness of the conventional (Q, r) model in managing production-inventory systems with finite capacity, stochastic demand, and stochastic order processing times. We show that, for systems with finite production capacity, order replenishment lead times are highly sensitive to loading and order quantity. Consequently, the choice of optimal order quantity and optimal reorder point can vary significantly from those obtained under the usual assumption of a load-independent lead time. More importantly, we show that for a given (Q, r) policy the conventional model can grossly under or over-estimate the actual cost of the policy. In cases where a setup time is associated with placing a production order, we show that the optimal (Q, r) policy derived from the conventional model can, in fact, be infeasible.

• Proceedings of the KIEE Conference
• /
• 1990.07a
• /
• pp.96-99
• /
• 1990

Recently, electric energy consumption pattern shows very high peak load with low load factor. This Load pattern have made electric utilities be interested in Load Management, many studies are reported. But most of these studies are concerned with Rate - Load shape relation, a few of these are concerned with generating cost reduction. In this study, the effect of Load Management is incorporated to establish optimal Generation Expansion Planning. Using avoided cost, optimal generation expansion planning is achieved to make maximum avoided cost of Electric utility. Dynamic programming technique is used to solve this algorithm.

• Journal of Korean Society of Water and Wastewater
• /
• v.29 no.2
• /
• pp.223-231
• /
• 2015

District Metered Area (DMA) construction is one of the most cost effective alternatives for management of water loss (i.e., water leakage) and energy consumption (i.e., water pressure) in water distribution systems. Therefore, it's being implemented to numerous new and existing water distribution systems worldwide. However, due to the complexity of water distribution systems, especially large-scale and highly looped systems, it is still very difficult to define the optimal boundary of DMAs considering all the aspects of water distribution system management requirements. In this study, a DMA design methodology (or a DMA design model) was developed with Geographic Information Systems (GIS) and hydraulic distribution system model to determine the optimal DMA boundary.

• Korean Journal of Construction Engineering and Management
• /
• v.8 no.6
• /
• pp.235-245
• /
• 2007

This research study presents the development and application of an Elitist Genetic Algorithm (Elitist GA) for solving the resource-constrained project scheduling problem, which is one of the most challenging problems in construction engineering. Main features of the developed algorithm are that the elitist roulette selection operator is developed to preserve the best individual solution for the next generation so as to obtain the improved solution, and that parallel schedule generation scheme is used to generate a feasible solution to the problem. The experimental results on standard problem sets indicate that the proposed algorithm not only produces reasonably good solutions to the problems over the heuristic method and other GA, but also can find the optimal and/or near optimal solutions for the large-sized problems with multiple resources within a reasonable amount of time that will be applicable to the construction industry. This paper will help researchers and/or practitioners in the construction project scheduling software area with alternative means to find the optimal schedules by utilizing the advantages of the Elitist GA.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.31 no.2
• /
• pp.129-140
• /
• 2006

Quantity Flexibility contract coordinates individually motivated supplier and buyer to the systemwide optimal outcome by effectively allocating the costs of market demand uncertainty. The main feature of the contract is to couple the buyer's commitment to purchase no less than a certain percentage below the forecast with the supplier's guarantee to deliver up to a certain percentage above. In this paper we refine the previous models by adding some realistic features including the upper and lower limits of the purchase. We also incorporate purchase and canceling costs in a cost function to reflect the real world contracting process more accurately. To obtain the solution of the model, we derive a condition for extreme points using the Leibniz's rule and construct an algorithm for finding the optimal solution of the model. Several examples illustrating the algorithm show that the approach is valid and efficient.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.24 no.4
• /
• pp.343-350
• /
• 2012

The major goal of building energy management is to minimize the energy consumption while maintaining the comfortable environment condition. Nowadays building energy management to save HVAC energy and so on is the most critical issue for existing building service branch with high efficiency equipments and their optimal operation. The effects on the building energy savings of the building equipment retrofit and the improvement of its operation method, especially in the field of HVAC system, were analyzed in this study for domestic small and/or medium sized buildings. Over 8.8% of energy saving was achieved compared withe total energy consumption in commercial building. These results could be used for reasonable maintenance and efficient management of the various building service equipments and related systems.