• Journal of the Korean Operations Research and Management Science Society
• /
• v.24 no.2
• /
• pp.121-134
• /
• 1999

In this paper, I propose a hybrid genetic algorithm(HGAM) incorporating a greedy interchange local optimization procedure for the multiobjective vehicle scheduling problems with service due times where three conflicting objectives of the minimization of total vehicle travel time, total weighted tardiness, and fleet size are explicitly treated. The vehicle is allowed to visit a node exceeding its due time with a penalty, but within the latest allowable time. The HGAM applies a mixed farming and migration strategy in the evolution process. The strategy splits the population into sub-populations, all of them evolving independently, and applys a local optimization procedure periodically to some best entities in sub-populations which are then substituted by the newly improved solutions. A solution of the HCAM is represented by a diploid structure. The HGAM uses a molified PMX operator for crossover and new types of mutation operator. The performance of the HGAM is extensively evaluated using the Solomons test problems. The results show that the HGAM attains better solutions than the BC-saving algorithm, but with a much longer computation time.

• Journal of the Korean Society for Precision Engineering
• /
• v.14 no.3
• /
• pp.89-97
• /
• 1997

A genetic algorithm (GA) is a stochastic direct search strategy that mimics the process of genetic evolution. The GA applied herein works on a population of structural designs at any one time, and uses a structured information exchange based on the principles of natural selection and wurvival of the fittest to recombine the most desirable features of the designs over a sequence of generations until the process converges to a "maximum fitness" design. Principles of genetics are adapted into a search procedure for structural optimization. The methods consist of three genetics operations mainly named selection, cross- over and mutation. In this study, a method of finding the optimum topology of truss/beam structure is pro- posed by using the GA. In order to use GA in the optimum topology problem, chromosomes to FEM elements are assigned, and a penalty function is used to include constraints into fitness function. The results show that the GA has the potential to be an effective tool for the optimal design of structures accounting for sizing, geometrical and topological variables.variables.

• Journal of the Korea Safety Management & Science
• /
• v.9 no.1
• /
• pp.77-84
• /
• 2007

This study was planned to investigate what the main factor of the regulation compliance of inspection on harmful machine, instrument and equipment by industrial safety and health act is. This study subject was composed of three groups as employers, employees of manufacturing and using the harmful machine and safety inspectors. Manufacturing workplace were 236 places, using workplace were 201 places and the safety inspectors were 100 people. The study subject was sampled by stratified random sampling considering the type of harmful Machine. Data for analysis is collected from each sample using interview with structured questionnaires. Compliance is measured by 2, 3, and 4 point scale composed by 8 sub items such as general perception, understanding, clearness, necessity, relevancy, implementation, penalty, and general compliance of the regulation. The level of 8 items of employer's compliance are not differentiated among three groups. The determining factors for inspection observance of the workplace using the harmful Machine were understanding, penalty and cognized compliance. The determining factors for inspection observance of the workplace manufacturing the harmful Machine were understanding and object conformity. These results show that the strategy to adapt the regulated group to inspection regulation will be the elevation of understanding for regulation first of all.

• IE interfaces
• /
• v.17 no.4
• /
• pp.472-481
• /
• 2004

In this paper, we propose a linear programming model of supply planning process for the supply chain collaboration strategy of a company. The amount of its supplying quantity relies on outsourcing suppliers heavily. Conversely, the revenues of those suppliers are highly dependent on the supplying quota from the supply network planning of the company. In order to keep the supply stable through collaboration, the company builds such a policy to guarantee the fairness on revenue between the supplies. For this, the supply network plan should keep the capacity utilization ratio even for all the suppliers. But the production capacities are different and the distribution of molds is disproportional through suppliers, so the supply network plan is not easily established with simple arithmetic processes. Therefore, we developed the linear programming model with those target function and constraints minimizing the costs for holding inventory and penalty of delayed delivery, simultaneously guaranteeing the even capacity utilization through suppliers. The proposed model has been applied to real case and the evaluation for the planning result from the model would be followed in order to make sure that our model guarantee on extracting the supply network plan subordinated to the policy. Also we mention about further studies for improvement of the model.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.2
• /
• pp.514-537
• /
• 2020

Wireless sensor network (WSN) is a distributed network composed of many sensory nodes. It is precisely due to the clustering unevenness and cluster head election randomness that the energy consumption of WSN is excessive. Therefore, a many-objective optimization WSN energy balance model is proposed for the first time in the clustering stage of LEACH protocol. The four objective is considered that the cluster distance, the sink node distance, the overall energy consumption of the network and the network energy consumption balance to select the cluster head, which to better balance the energy consumption of the WSN network and extend the network lifetime. A many-objective optimization algorithm to optimize the model (LEACH-ABF) is designed, which combines adaptive balanced function strategy with penalty-based boundary selection intersection strategy to optimize the clustering method of LEACH. The experimental results show that LEACH-ABF can balance network energy consumption effectively and extend the network lifetime when compared with other algorithms.

• Journal of Korean Institute of Industrial Engineers
• /
• v.39 no.6
• /
• pp.562-576
• /
• 2013

Power TAC (Power Trading Agent Competition) is an agent-based simulation for competitions between electricity brokering agents on the smart grid. To win the competition, agents obtain electricity from the electricity wholesale market among the power plants. In this operation, a key to success is balancing the demand of the customer and the supply from the plants because any imbalance results in a significant penalty to the brokering agent. Given the bidding on the wholesale market requires the price and the quantity on the electricity, this paper proposes four different price estimation strategies: exponentially moving average, linear regression, fuzzy logic, and support vector regression. Our evaluations with the competition simulation show which strategy is better than which, and which strategy wins in the free-for-all situations. This result is a crucial component in designing an electricity brokering agent in both Power TAC and the real world.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.8
• /
• pp.2783-2804
• /
• 2021

In the network function virtualization environment, dynamic changes in network traffic will lead to the dynamic changes of service function chain resource demand, which entails timely dynamic adjustment of service function chain resource configuration. At present, most researches solve this problem through virtual network function migration and link rerouting, and there exist some problems such as long service interruption time, excessive network operation cost and high penalty. This paper proposes a dynamic adjustment method of service function chain resource configuration for the dynamic changes of network traffic. First, a dynamic adjustment request of service function chain is generated according to the prediction of network traffic. Second, a dynamic adjustment strategy of service function chain resource configuration is determined according to substrate network resources. Finally, the resource configuration of a service function chain is pre-adjusted according to the dynamic adjustment strategy. Virtual network functions combination and virtual machine reusing are fully considered in this process. The experimental results show that this method can reduce the influence of service function chain resource configuration dynamic adjustment on quality of service, reduce network operation cost and improve the revenue of service providers.

• Health Policy and Management
• /
• v.27 no.2
• /
• pp.121-127
• /
• 2017

The effort to measure and improve the quality of healthcare is a common health policy issue worldwide. Korean Value Incentive Programme is one of that effort, but some concerns exist. Compared to pay for performance program in other countries, it measures healthcare quality with relatively narrow performance domain using a small number of clinical indicators. It was designed without involving hospitals and other key stakeholder, and program participation was mandated. Highest and lowest performers get bonus and penalty using relative ranking. As a suggestion for development, the direction for quality management at the national level should be given first. Therefore the philosophy or strategy for quality improvement should be reflected to the program. And various domains and indicators of healthcare quality should be developed with active communication with healthcare providers. The evaluation method is necessary to be changed to provide achievable goal to the healthcare providers and attract quality improvement.

• Proceedings of the Korea Database Society Conference
• /
• 1999.06a
• /
• pp.195-202
• /
• 1999

본 논문은 배전 계통에서 부하 제약조건과 운전 제약조건을 고려한 손실 감소와 부하 평형에 대해 시뮬레이티드 어닐링 알고리즘을 적용한 재구성 방법을 서술하였다. 네트워크 재구성은 수많은 연계 개폐기와 구분 개폐기의 조합에 의해 이루어지기 때문에 조합적인 최적화 문제이다. 이러한 문제는 수많은 조합에 제약조건까지 있어 해를 구하기가 쉽지 않을 뿐 아니라 국소 해에 빠질 가능성이 많다. 따라서 신경망 중에서 제약조건에 따라 신경망 구조에 영향을 미치지 않으면서 전역 최소해에 수렴하는 특성을 가진 시뮬레이티드 어닐링 기법을 이용하여 배전 계통의 선로를 재구성하였다. 시뮬레이티드 어닐링은 이론적으로 최적해가 보장되지만 무한대의 시간이 걸리기 때문에 현실적으로 적용할 때 해 공간을 탐색하는 규칙과 온도를 적절히 내리는 냉각 스케줄(cooling schedule)이 중요하다. 본 논문에서는 알고리즘 상에서 제약조건 위반 여부를 점검할 수 있는 제약조건과 페널티 상수(penalty factor)를 통해 목적함수에 반영하는 제약조건으로 나누어 모든 후보해를 가능해가 되게 하였고 기존에 사용되던 Kirkpatrick의 냉각 스케줄 대신에 후보해의 통계적 처리에 의해 온도를 내리는 다항-시간 냉각 스케줄(polynomial-time cooling schedule)을 사용하여 수행시간을 단축하고 수렴성을 높였다. 제안한 알고리즘의 효용성을 입증하기 위해 32, 69모선 예제 계통으로 테스트하였다.

• Journal of Advanced Marine Engineering and Technology
• /
• v.24 no.2
• /
• pp.50-56
• /
• 2000

This paper presents the design of an optimal state feedback controller for container cranes under some design specifications. To do this, the nonlinear equation of a container crane system is linearized and then augmented to eliminate the steady-state error, and some constraints are derived from the design specifications. Designing the controller involves a constrained optimization problem which classical gradient-based methods have difficulties in handling. Therefore, a real-coding genetic algorithm incorporating the penalty strategy is used. The responses of the proposed control system are compared with those of the unconstrained optimal control system to illustrate the efficiency.