• The KIPS Transactions:PartC
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• v.11C no.5
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• pp.677-682
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• 2004

In the present paper routing and wavelength assignment (RWA) in optical WDM networks is considered. Previous techniques based on the combination of integer linear programming and graph coloring are complex and require extensive use of heuristics. Such methods are mostly slow and sometimes impossible to get results due to infeasibility. An alternative approach applied to RWA employs on the greedy algorithm for obtaining the maximum edge disjoint paths. Even though this approach is fast, it produces a solution for any connection request, which is very far from the optimal utilization of wavelengths. We propose a novel algorithm, which is based on the maximum flow technique to obtain the maximum quantity of edge, disjoint paths. Here we compare the offered method with previous maximum edge disjoint paths algorithms ap plied to the RWA.

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

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

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

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.9
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• pp.681-688
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• 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 the Korea Academia-Industrial cooperation Society
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• v.19 no.8
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• pp.312-321
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• 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 Korean Society of Transportation
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• v.18 no.4
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• pp.7-18
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• 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).

• Korean Chemical Engineering Research
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• v.57 no.1
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• pp.51-57
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• 2019

A plant layout problem has a large impact on the overall construction cost of a plant. When determining a plant layout, various constraints associating with safety, environment, sufficient maintenance area, passages for workers, etc have to be considered together. In general plant layout problems, the main goal is to minimize the length of piping connecting equipments as satisfying various constraints. Since the process may suffer from the heat and friction loss, the piping length between equipments should be shorter. This problem can be represented by the mathematical formulation and the optimal solutions can be investigated by an optimization solver. General researches have overlooked many constraints such as maintenance spaces and safety distances between equipments. And, previous researches have tested benchmark processes. What the lack of general researches is that there is no realistic comparison. In this study, the plant layout of a real industrial C3MR (Propane precooling Mixed Refrigerant) process is studied. A MILP (Mixed Integer Linear Programming) including various constraints is developed. To avoid the violation of constraints, penalty functions are introduced. However, conventional optimization solvers handling the derivatives of an objective functions can not solve this problem due to the complexities of equations. Therefore, the PSO (Particle Swarm Optimization), which investigate an optimal solutions without differential equations, is selected to solve this problem. The results show that a proposed method contributes to saving the capital expenditures.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.169-180
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• 2015

Recently, scheduling problems with position-dependent processing times have received considerable attention in the literature, where the processing times of jobs are dependent on the processing sequences. However, they did not consider cases in which each processed job has different learning or aging ratios. This means that the actual processing time for a job can be determined not only by the processing sequence, but also by the learning/aging ratio, which can reflect the degree of processing difficulties in subsequent jobs. Motivated by these remarks, in this paper, we consider a two-agent single-machine scheduling problem with linear job-dependent position-based learning effects, where two agents compete to use a common single machine and each job has a different learning ratio. Specifically, we take into account two different objective functions for two agents: one agent minimizes the total weighted completion time, and the other restricts the makespan to less than an upper bound. After formally defining the problem by developing a mixed integer non-linear programming formulation, we devise a branch-and-bound (B&B) algorithm to give optimal solutions by developing four dominance properties based on a pairwise interchange comparison and four properties regarding the feasibility of a considered sequence. We suggest a lower bound to speed up the search procedure in the B&B algorithm by fathoming any non-prominent nodes. As this problem is at least NP-hard, we suggest efficient genetic algorithms using different methods to generate the initial population and two crossover operations. Computational results show that the proposed algorithms are efficient to obtain near-optimal solutions.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.945-949
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• 2004

These days there are so many scheduling systems or softwares. But only few scheduling systems have succeeded in the market. In spite of powerful engine and functions, those systems have difficulties to be applied in real processes. In real processes, there are various constraints caused by physical or systematical environments of plants. Those constraints are too many to be handled in the system. This problem makes it difficult for the system to represent the details of processes. In order to resolve this problem, we have developed a specialized scheduling system for a target process. The system could be developed by the experts for target process and researchers for scheduling. In this study, a scheduling system for PVC process has been developed as an MILP (Mixed integer linear programming) model and coded in $Fortran^{TM}$. The scheduling system has been applied to two processes, which have different characteristics. Simulation results indicate that the profit of the target process can be increased by about 5% by implementing the scheduling system.