• Proceedings of the Safety Management and Science Conference
• /
• 2010.11a
• /
• pp.245-256
• /
• 2010

최근 들어 안전관리의 패러다임은 사후분석에서 사전예방으로 바뀌고 있다. 이러한 추세에 맞추어 본질적인 안전관리에 대한 관심이 늘어나고 있다. 공정에 본질적인 안전을 추구하는 방법은 크게 5가지로 나누어 질 수 있으며, 공정의 배치를 통해서 사고를 영향을 최소화하는 방법은 공정의 설계단계에서 적용할 수 있는 좋은 방법이다. 본 연구에서는 공정의 설비가 가지는 위험성을 기반으로 안전거리에 대한 지침을 제시하고 있다. 사고결과와 사고발생빈도를 기반으로 개인적 위험성(Individual Risk: IR)을 계산하였으며, 계산된 값을 기반으로 최적의 안전거리 계산을 수행할 수 있었다. 계산된 IR과 문헌에서 제시된 안전거리를 바탕으로 작업자가 거주하는 건물과 공정경계 까지의 적절한 거리와 설비간의 최적의 거리를 계산하게 된다. Mixed Integer Linear Programming(MILP)를 이용하여 각각설비의 안전거리가 확보된 시설물 배치와 최소 부지 면적 등을 알 수가 있다. 이 연구를 통해 최적화된 부지면적과 파이프라인의 시설물 배치는 물론 공정건설이나 초기 디자인 단계 및 안전성확보측면에서 본질적인 안전을 구현하는데 유용하게 적용될 수 있다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2016.04a
• /
• pp.464-465
• /
• 2016

This paper analyzes the capabilities of multi-agent system (MAS) technology for the optimal multi-microgrids (MMGs) operation in grid-connected mode. In this system, communication among microgrids (MGs) is realized by developing a modified contract net protocol (MCNP) based on agent communication language (ACL) messages. Moreover, a two-stage mathematical model is proposed based on mixed integer linear programming (MILP) for local optimization in each MG, and global optimization in energy management system.

• Journal of Korea Water Resources Association
• /
• v.42 no.8
• /
• pp.643-657
• /
• 2009

The major reason to construct large dams is to store surplus water during rainy seasons and utilize it for water supply in dry seasons. Reservoir storage has to meet a pre-defined target to satisfy water demands and cope with a dry season when the availability of water resources are limited temporally as well as spatially. In this study, a Hedging rule that reduces total reservoir outflow as drought starts is applied to alleviate severe water shortages. Five stages for reducing outflow based on the current reservoir storage are proposed as the Hedging rule. The objective function is to minimize the total discrepancies between the target and actual reservoir storage, water supply and demand, and required minimum river discharge and actual river flow. Mixed Integer Linear Programming (MILP) is used to develop a multi-reservoir operation system with the Hedging rule. The developed system is applied for the Han River basin that includes four multi-purpose dams and one water supplying reservoir. One of the fours dams is primarily for power generation. Ten-day-based runoff from subbasins and water demand in 2003 and water supply plan to water users from the reservoirs are used from "Long Term Comprehensive Plan for Water Resources in Korea" and "Practical Handbook of Dam Operation in Korea", respectively. The model was optimized by GAMS/CPLEX which is LP/MIP solver using a branch-and-cut algorithm. As results, 99.99% of municipal demand, 99.91% of agricultural demand and 100.00% of minimum river discharge were satisfied and, at the same time, dam storage compared to the storage efficiency increased 10.04% which is a real operation data in 2003.

• Korean Chemical Engineering Research
• /
• v.52 no.5
• /
• pp.603-612
• /
• 2014

Lots of networks are constructed in a large scale industrial complex. Each network meet their demands through production or transportation of materials which are needed to companies in a network. Network directly produces materials for satisfying demands in a company or purchase form outside due to demand uncertainty, financial factor, and so on. Especially utility network and hydrogen network are typical and major networks in a large scale industrial complex. Many studies have been done mainly with focusing on minimizing the total cost or optimizing the network structure. But, few research tries to make an integrated network model by connecting utility network and hydrogen network In this study, deterministic mixed integer linear programming model is developed for integrating utility network and hydrogen network. Steam Methane Reforming process is necessary for combining two networks. After producing hydrogen from Steam-Methane Reforming process whose raw material is steam vents from utility network, produced hydrogen go into hydrogen network and fulfill own needs. Proposed model can suggest optimized case in integrated network model, optimized blueprint, and calculate optimal total cost. The capability of the proposed model is tested by applying it to Yeosu industrial complex in Korea. Yeosu industrial complex has the one of the biggest petrochemical complex and various papers are based in data of Yeosu industrial complex. From a case study, the integrated network model suggests more optimal conclusions compared with previous results obtained by individually researching utility network and hydrogen network.

• Industrial Engineering and Management Systems
• /
• v.6 no.2
• /
• pp.136-145
• /
• 2007

The selection of suppliers and the determination of order quantities to be placed with those suppliers are important decisions in a supply chain. In this research, a non-linear mixed integer programming model is presented to select suppliers and determine the order quantities. The model considers the purchasing cost which takes into account quantity discount, the cost of transportation, the fixed cost for establishing suppliers, the cost for holding inventory, and the cost of receiving poor quality parts. The capacity constraints for suppliers, quality and lead-time requirements for the parts are also taken into account in the model. Since the purchasing cost, which is a decreasing step function of order quantities, introduces discontinuities to the non-linear objective function, it is not easy to employ traditional optimization methods. Thus, a heuristic algorithm, called particle swarm optimization (PSO), is used to find the (near) optimal solution. However, PSO usually generates initial solutions randomly. To improve the PSO solution quality, a heuristic procedure is proposed to find an initial solution based on the average unit cost including transportation, purchasing, inventory, and poor quality part cost. The results show that PSO with the proposed initial solution heuristic provides better solutions than those with PSO algorithm only.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.8
• /
• pp.312-321
• /
• 2018

The Korean DR market proposes suppression of peak demand under reliability crisis caused a natural disaster or unexpected power plant accidents as well as saving power plant construction costs and expanding amount of reserve as utility's perspective. End-user is notified a DR event signal DR execution before one hour, and executes DR based on requested amount of load reduction. This paper proposes a DR energy management algorithm that can be scheduled the optimal operations of chiller system and ESS in the next day considering the TOU tariff and DR scheme. In this DR algorithm is divided into two scheduling's; day-ahead operation scheduling with temperature forecasting error and operation rescheduling on DR operation. In day-ahead operation scheduling, the operations of DR resources are scheduled based on the finite number of ambient temperature scenarios, which have been generated based on the historical ambient temperature data. As well as, the uncertainties in DR event including requested amount of load reduction and specified DR duration are also considered as scenarios. Also, operation rescheduling on DR operation day is proposed to ensure thermal comfort and the benefit of a COB owner. The proposed method minimizes the expected energy cost by a mixed integer linear programming (MILP).

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.41 no.9
• /
• pp.681-688
• /
• 2013

Several problems caused by inevitable increment of airplane have been issued. The most effective solution to solve the issues is considered as establishing appropriate Air Traffic Management (ATM) that reduces aircraft's delay at an airport and intensify the airport's capacity. The purpose of this paper is to produce the optimum aircraft schedules that maximize the aircraft throughput by smooth air traffic flow near terminal area of an airport In this paper, mathematical formulations of the scheduling problem are firstly specified. Based on the mathematical modelling, an Optimization-Based Flight Scheduler that provides the optimum flight schedules for arriving aircraft is developed by introducing the Mixed Integer Linear Programming(MILP) and the Genetic Algorithms(GA). With this scheduler, we calculated the optimum schedules to compare to real schedule data from an Incheon Airport. As a result, it is validated that aircraft throughput produced by the optimum schedule is much better than that of the schedule from the Incheon airport. The optimization-based flight scheduler is expected to deal with problems due to the aircraft saturation in near future.

• Journal of Korean Society of Transportation
• /
• v.18 no.4
• /
• pp.7-18
• /
• 2000

KS-SIGNAL, a traffic signal optimization model for coordinated arterials, is an optimization model using the mixed integer linear Programming that minimizes total delay on arterials by optimizing left-turn Phase sequences. However, the Previous version of KS-SIGNAL had a difficulty in reducing computation speed because the related variables and constraints multiply rapidly in accordance with the increase of intersections. This study is designed to propose a new model, improving optimizing computation speed in KS-SIGMAl, and evaluate it. This Paper Puts forth three kinds of methodological approaches as to achieve the above goals. At the first step to reduce run-time in the proposed model objective function and a few constraints are Partially modified, which replaces variable in related to queue clearance time with constant, by using thru-movements at upstream intersection and the length of red time at downstream intersection. The result shows that the run-time can be reduced up to 70% at this step. The second step to load the library in LINDO for Windows, in order to solve mixed integer linear programming. The result suggests that run-time can be reduced obviously up to 99% of the first step result. The third step is to add constraints in related to left-turn Phase sequences. The proposed methodological approach, not optimizing all kinds of left-turn sequences, is more reasonable than that of previous model , only in the view of reducing run-tim. In conclusion, run-time could be reduced up to 30% compared with the second results. This Proposed model was tested by several optimization scenarios. The results in this study reveals that signal timing plan in KS-SIGNAL is closer to PASSER-II (bandwidth maximizing model) rather than to TRANSYT-7F(delay minimizing model).

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.5
• /
• pp.1567-1587
• /
• 2014

Virtual Machine (VM) resource management is crucial to satisfy the Quality of Service (QoS) demands of various multimedia services in a media cloud platform. To this end, this paper presents a VM resource allocation model that dynamically and optimally utilizes VM resources to satisfy QoS requirements of media-rich cloud services or applications. It additionally maintains high system utilization by avoiding the over-provisioning of VM resources to services or applications. The objective is to 1) minimize the number of physical machines for cost reduction and energy saving; 2) control the processing delay of media services to improve response time; and 3) achieve load balancing or overall utilization of physical resources. The proposed VM allocation is mapped into the multidimensional bin-packing problem, which is NP-complete. To solve this problem, we have designed a Mixed Integer Linear Programming (MILP) model, as well as heuristics for quantitatively optimizing the VM allocation. The simulation results show that our scheme outperforms the existing VM allocation schemes in a media cloud environment, in terms of cost reduction, response time reduction and QoS guarantee.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.6
• /
• pp.2282-2303
• /
• 2021

To solve the problems of heavy computing load and system transmission pressure in energy internet (EI), we establish a three-tier cloud-edge integrated EI network based on a cloud-edge collaborative computing to achieve the tradeoff between energy consumption and the system delay. A joint optimization problem for resource allocation and task offloading in the threetier cloud-edge integrated EI network is formulated to minimize the total system cost under the constraints of the task scheduling binary variables of each sensor node, the maximum uplink transmit power of each sensor node, the limited computation capability of the sensor node and the maximum computation resource of each edge server, which is a Mixed Integer Non-linear Programming (MINLP) problem. To solve the problem, we propose a joint task offloading and resource allocation algorithm (JTOARA), which is decomposed into three subproblems including the uplink transmission power allocation sub-problem, the computation resource allocation sub-problem, and the offloading scheme selection subproblem. Then, the power allocation of each sensor node is achieved by bisection search algorithm, which has a fast convergence. While the computation resource allocation is derived by line optimization method and convex optimization theory. Finally, to achieve the optimal task offloading, we propose a cloud-edge collaborative computation offloading schemes based on game theory and prove the existence of Nash Equilibrium. The simulation results demonstrate that our proposed algorithm can improve output performance as comparing with the conventional algorithms, and its performance is close to the that of the enumerative algorithm.