• 한국경영과학회지
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• 제39권2호
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• pp.37-48
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• 2014

Fighter squadron flight scheduling is the integrated air operation plan that is an important role for improving pilot's flight skill and maintaining combat readiness by efficient using available all air resources including pilot, aircrafts, air-weapons, fuel and supporting facilities etc. Korea airforce, however, has a limit as to an effective flight operation due to manual flight scheduling with scheduler's own experience and intuition. Therefore, in our study, we propose the optimization model of flight scheduling based on mixed integer programming. This model includes several constraints of realistic and essential quantified data related with flight schedule and can assign appropriate pilots optimally which are distinctive three type's solutions : flight, alert and duty crew schedules. Proposed solution method can be improved pilot's capability and allocated further air resources systematically and efficiently. In addition, it can be reduced a workload of flight scheduler and minimized obstructed factors of flight safety. Finally, we demonstrate the experiment's results for the check of efficiency and validity of this model.

• 대한전기학회논문지:전력기술부문A
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• 제48권3호
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• pp.234-240
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• 1999

This paper presents a new approach for large-scale generator maintenance scheduling optimizations. The generator preventive maintenance scheduling problems are typical discrete dynamic n-dimensional vector optimization ones with several inequality constraints. The considered objective function to be minimized a subset of{{{{ { R}^{n } }}}} space is the variance (i.g., second-order momentum) of operating reserve margin to levelize risk or reliability during a year. By its nature of the objective function, the optimal solution can only be obtained by enumerating all combinatorial states of each variable, a task which leads to computational explosion in real-world maintenance scheduling problems. This paper proposes a new priority search mechanism based on each generator's discrete sensitivity value which was analytically developed in this study. Unlike the conventional capacity-based priority search, it can prevent the local optimal trap to some extents since it changes dynamically the search tree in each iteration. The proposed method have been applied to two test systems (i.g., one is a sample system with 10 generators and the other is a real-world lage scale power system with 280 generators), and the results anre compared with those of the conventional capacith-based search method and combinatorial optimization method to show the efficiency and effectiveness of the algorithm.

• 전기학회논문지
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• 제57권4호
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• pp.692-699
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• 2008

Semiconductor research and development(R&D) fabs are very different than production fabs in many ways such as the scales of production, job priority, production methods, and performance measures. Efficient operations of R&D fabs are very important to the development of new product, process stability, high yield, and ultimately company competitiveness. This paper proposes the fab-wide scheduling method for operational optimization of the R&D fabs. Most scheduling systems of semiconductor fabs have only focused on maximizing throughput of each separated areas without considering WIP(works in process) flows of entire fab. In this paper, we proposes the a fab-wide scheduling system which schedules all lots to entire fab equipment at once. We develop the MIP(mixed integer programing) model which allocates the lots to production equipment considering many constraints of all processes and the CP(constraint programming) model which determines the sequences of the lots in the production equipment. The proposed FAB-wide scheduling model is applied to the newly constructed R&D fab. As a result, we have accomplished the system based automated job reservation, decrease of the hot lot delay, increase of the queue time satisfaction, the high throughput by maximizing the batch sizes, decrease of the WIP TAT(Turn Around Time).

• 국제학술발표논문집
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• The 2th International Conference on Construction Engineering and Project Management
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• pp.530-539
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• 2007

Many construction projects such as highways, pipelines, tunnels, and high-rise buildings typically contain repetitive activities. Research has shown that the Critical Path Method (CPM) is not efficient in scheduling linear construction projects that involve repetitive tasks. Linear Scheduling Method (LSM) is one of the techniques that have been developed since 1960s to handle projects with repetitive characteristics. Although LSM has been regarded as a technique that provides significant advantages over CPM in linear construction projects, it has been mainly viewed as a graphical complement to the CPM. Studies of scheduling linear construction projects with resource consideration are rare, especially with multiple resource constraints. The objective of this proposed research is to explore a resource assignment mechanism, which assigns multiple critical resources to all activities to minimize the project duration while satisfying the activities precedence relationship and resource limitations. Resources assigned to an activity are allowed to vary within a range at different stations, which is a combinatorial optimization problem in nature. A heuristic multiple resource allocation algorithm is explored to obtain a feasible initial solution. The Simulated Annealing search algorithm is then utilized to improve the initial solution for obtaining near-optimum solutions. A housing example is studied to demonstrate the resource assignment mechanism.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.145-145
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• 2021

Water distribution networks (WDNs) are designed to satisfy water requirement of an urban community. One of the central issues in human history is providing sufficient quality and quantity of water through WDNs. A WDN consists of a great number of pipelines with different ages, lengths, materials, and sizes in varying degrees of deterioration. The available annual budget for rehabilitation of these infrastructures only covers part of the network; thus it is important to manage the limited budget in the most cost-effective manner. In this study, a novel pipe replacement scheduling approach is proposed in order to smooth the annual investment time series based on a life cycle cost assessment. The proposed approach is applied to a real WDN currently operating in South Korea. The proposed scheduling plan considers both the annual budget limitation and the optimum investment on pipes' useful life. A non-dominated sorting genetic algorithm is used to solve a multi-objective optimization problem. Three decision-making objectives, including the minimum imposed LCC of the network, the minimum standard deviation of annual cost, and the minimum average age of the network, are considered to find optimal pipe replacement planning over long-term time period. The results indicate that the proposed scheduling structure provides efficient and cost-effective rehabilitation management of water network with consistent annual budget.

• Journal of Mechanical Science and Technology
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• 제20권12호
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• pp.2115-2123
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• 2006

The paper deals with the identification of Pareto optimal solutions using GA based coevolution in the context of multiobjective optimization. Coevolution is a genetic process by which several species work with different types of individuals in parallel. The concept of cooperative coevolution is adopted to compensate for each of single objective optimal solutions during genetic evolution. The present study explores the GA based coevolution, and develops prescribed and adaptive scheduling schemes to reflect design characteristics among single objective optimization. In the paper, non-dominated Pareto optimal solutions are obtained by controlling scheduling schemes and comparing each of single objective optimal solutions. The proposed strategies are subsequently applied to a three-bar planar truss design and an energy preserving flywheel design to support proposed strategies.

• International Journal of Automotive Technology
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• 제8권1호
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• pp.39-48
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• 2007

This paper addresses the problem of period and priority assignment in networked control systems (NCSs) using a fixed priority scheduler. The problem of assigning periods and priorities to tasks and messages is formulated as an optimization problem to allow for a systematic approach. The temporal characteristics of an NCS should be considered by defining an appropriate performance index (PI) which represents the temporal behavior of the NCS. In this study, the sum of the end-to-end response times required to process all I/Os with precedence relationships is defined as a PI. Constraints are derived from the task and message deadline requirements to guarantee schedulability. Genetic algorithms are used to solve this constrained optimization problem because the optimization formulation is discrete and nonlinear. By considering the effects of communication, an optimum set of periods and priorities can be holistically derived.

• Korean Chemical Engineering Research
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• 제58권3호
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• pp.346-355
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• 2020

의약 중간체 제조 공장을 포함한 정밀 화학 산업에서 생산 계획 및 전사적 자원 관리(enterprise resource planning) 관한 의사 결정은 기업 운영 효율성 최적화에 매우 주요한 연구 주제이다. 기존의 의사 결정 시스템은 공장 간의 자원관리와 공장내 생산 계획이 분리되어, 전사적 관점에서의 전역 해를 도출하는데 한계가 있다. 본 연구에서는 무선 식별 시스템(Radio Frequency Identification; RFID) 기반의 실시간 물류 관리 시스템을 이용하여 의약품 중간체 산업의 전사적 자원 관리와 최적 생산 계획 수립을 동시에 수행할 수 있는 의사결정 플랫폼을 개발하고, 실제 제조 공정에 적용하여 그 효과를 분석한다. 기존의 분리된 운영 체제와는 달린 본 연구에서 제안하는 통한 의사결정 플랫폼은 원료 주문 및 운송 시간에 관한 정보가 RFID 기술을 통해 제조 공정 생산 계획 수립의 핵심 데이터로 사용됨으로써, 별도의 재고 관리 시설 없이 공장간 물류 현황에 대응하여 최적 생산 계획이 수립된다. 이를 위하여 제품 생산 시간 최소화를 목적 함수로 설정하고, 마감 기한 및 주문량에 대한 제약조건 등을 포함한 혼합정수선형계획 모델을 개발하였다. 이후 개발된 최적화 모델을 실제 의약품 중간체 생산 문제로 적용함으로써, 제안한 통합 의사결정 플랫폼의 효용성을 입증하였다. 본 연구 결과로 생산 시간 최적화를 위해 단순한 공정 조합을 필요로 하는 생산물이 먼저 제조되고 복잡한 공정 구조를 가진 생산물이 순차적으로 생산되는 생산 일정이 최적임을 확인하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 하계종합학술대회 논문집(2)
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• pp.459-462
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• 2004

In this paper, we present a reducing power consumption of a scheduling for module selection under the time constraint. A a reducing power consumption of a scheduling for module selection under the time constraint execute scheduling and allocation for considering the switching activity. The focus scheduling of this phase adopt Force-Directed Scheduling for low power to existed Force-Directed Scheduling. and it constructs the module selection RT library by in account consideration the mutual correlation of parameters in which the power and the area and delay. when it is, in this paper we formulate the module selection method as a multi-objective optimization and propose a branch and bound approach to explore the large design space of module selection. Therefore, the optimal module selection method proposed to consider power, area, delay parameter at the same time. The comparison experiment analyzed a point of difference between the existed FDS algorithm and a new FDS_RPC algorithm.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1993년도 춘계공동학술대회 발표논문 및 초록집; 계명대학교, 대구; 30 Apr.-1 May 1993
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• pp.109-118
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• 1993

This paper describes the management of knowledge base and optimization models using knowledge-assisted optimization model formulation system UNIK-OPT (UNIfied Knowledge-OPTimization). We will illustrate UNIK-OPT with the case of production scheduling in refinery.