• Title/Summary/Keyword: Cost Constraint

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A neural network with adaptive learning algorithm of curvature smoothing for time-series prediction (시계열 예측을 위한 1, 2차 미분 감소 기능의 적응 학습 알고리즘을 갖는 신경회로망)

  • 정수영;이민호;이수영
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.34C no.6
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    • pp.71-78
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    • 1997
  • In this paper, a new neural network training algorithm will be devised for function approximator with good generalization characteristics and tested with the time series prediction problem using santaFe competition data sets. To enhance the generalization ability a constraint term of hidden neuraon activations is added to the conventional output error, which gives the curvature smoothing characteristics to multi-layer neural networks. A hybrid learning algorithm of the error-back propagation and Hebbian learning algorithm with weight decay constraint will be naturally developed by the steepest decent algorithm minimizing the proposed cost function without much increase of computational requriements.

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Feasible Power Exchange between Russia and ROK Power Systems

  • Kim Jong-Yul;Lee Seung-Ryul;Yoon Jae-Young;Kim Ho-Yong
    • KIEE International Transactions on Power Engineering
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    • v.5A no.3
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    • pp.221-227
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    • 2005
  • This paper evaluates minimum and maximum power exchange considering economic and technical characteristics between Russia and ROK. First, we evaluate minimum power exchange to assure the economic feasibility by comparison with the total cost and benefit of the interconnected line. For evaluating maximum exchange power, system constraints are considered, which are examined through load flow and dynamic analysis by using the PSS/E program. As a result of these evaluations, we suggest the reasonable range of power exchange between ROK and Russia considering economic and technical constraints with the interconnection scenario that power system interconnection between ROK and Russia will be realized in the year 2010.

A Genetic Algorithm for Route Guidance System in Intermodal Transportation Networks with Time - Schedule Constraints (서비스시간 제한이 있는 복합교통망에서의 경로안내 시스템을 위한 유전자 알고리듬)

  • Chang, In-Seong
    • Journal of Korean Institute of Industrial Engineers
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    • v.27 no.2
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    • pp.140-149
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    • 2001
  • The paper discusses the problem of finding the Origin-Destination(O-D) shortest paths in internodal transportation networks with time-schedule constraints. The shortest path problem on the internodal transportation network is concerned with finding a path with minimum distance, time, or cost from an origin to a destination using all possible transportation modalities. The time-schedule constraint requires that the departure time to travel from a transfer station to another node takes place only at one of pre-specified departure times. The scheduled departure times at the transfer station are the times when the passengers are allowed to leave the station to another node using the relative transportation modality. Therefore, the total time of a path in an internodal transportation network subject to time-schedule constraints includes traveling time and transfer waiting time. In this paper, a genetic algorithm (GA) approach is developed to deal with this problem. The effectiveness of the GA approach is evaluated using several test problems.

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An Algorithm for Determining Consumable Spare Parts Requirement under Avialability Constraint (운용가용도 제약하에서의 소모성 예비부품의 구매량 결정을 위한 해법)

  • 오근태;나윤군
    • Journal of the Korea Society for Simulation
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    • v.10 no.3
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    • pp.83-94
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    • 2001
  • In this paper, the consumable spare parts requirement determination problem of newly procured equipment systems is considered. The problem is formulated as the cost minimization problem with operational availability constraint. Assuming part failure rate is constant during operational period, an analytical method is developed to obtain spare part requirements. Since this solution tends to overestimate the requirements, a fast search simulation procedure is introduced to adjust it to the realistic solution. The analytical solution procedure and the simulation procedure are performed recursively until a near optimal solution is achieved. The experimental results show that the near optimal solution is approached in a fairly short amount of time.

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FUZZY TRANSPORTATION PROBLEM WITH ADDITIONAL CONSTRAINT IN DIFFERENT ENVIRONMENTS

  • BUVANESHWARI, T.K.;ANURADHA, D.
    • Journal of applied mathematics & informatics
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    • v.40 no.5_6
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    • pp.933-947
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    • 2022
  • In this research, we presented the type 2 fuzzy transportation problem with additional constraints and solved by our proposed genetic algorithm model, and the results are verified using the softwares, genetic algorithm tool in Matlab and Lingo. The goal of our approach is to minimize the cost in solving a transportation problem with an additional constraint (TPAC) using the genetic algorithm (GA) based type 2 fuzzy parameter. We reduced the type 2 fuzzy set (T2FS) into a type 1 fuzzy set (T1FS) using a critical value-based reduction method (CVRM). Also, we use the centroid method (CM) to obtain the corresponding crisp value for this reduced fuzzy set. To achieve the best solution, GA is applied to TPAC in type 2 fuzzy parameters. A real-life situation is considered to illustrate the method.

A CP-BASED OPTIMIZATION MODEL FOR CONSTRUCTION RESCHEDULING PROBLEMS

  • Shu-Shun Liu;Kuo-Chuan Shih
    • International conference on construction engineering and project management
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    • 2005.10a
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    • pp.941-946
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    • 2005
  • It is essential for project managers to make schedule adjustment based on their professional experience, in terms of rescheduling action discussed in this paper. This paper discusses the topics of resource-constrained construction rescheduling by modifying the concepts of manufacturing rescheduling. Moreover, the influence factors of construction rescheduling problems are investigated and identified in this paper. According to initial schedule plan and present progress, a new rescheduling mechanism based on Constraint Programming (CP) techniques is developed to reschedule projects with the objective of minimizing total project cost or duration, under three rescheduling policies. Through case study, the behavior of three different rescheduling policies is analyzed and discussed in this paper.

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Optimization of Machining Process Using an Adaptive Modeling and Genetic Algorithms(1) -Simulation Study- (적응 모델링과 유전알고리듬을 이용한 절삭공정의 최적화(I) -모의해석-)

  • Ko, Tae Jo;Kim, Hee Sool;Kim, Do Gyun
    • Journal of the Korean Society for Precision Engineering
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    • v.13 no.11
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    • pp.73-81
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    • 1996
  • This paper presents a general procedure for the selection of the machining parameters for a given machine which provides the maximum material removal rate using a Genetic Algorithms(GAs). Some constraints were given in order to achieve desired surface integrity and cutting tool life conditions as wel as to protect machine tool. Such a constrained problem can be transformaed to unconstrained problem by associating a penalty with all constraint violations and the penalties are included in the function evaluation. Genetic Algorithms can be used for finding global optimum cutting conditions with respect to the above cost function transformed by pennalty function method. From the demonstration of the numerical results, it was found that the near optimal conditions could be obtained regardless of complex solution space such as cutting environment.

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Optimal Long-term Transmission Planning Algorithm using Non-linear Branch-and-bound Method (비선형 분산안전법을 이용한 최적장기송전계률 알고리)

  • 박영문;신중린
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.37 no.5
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    • pp.272-281
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    • 1988
  • The problem of optimal transmission system planning is to find the most economical locations and time of transmission line construction under the various constraints such as available rights-of-way, finances, the technical characteristics of power system, and the reliability criterion of power supply, and so on. In this paper the constraint of right-of-way is represented as a finite set of available rights-of-way. And the constructed for a unit period. The electrical constraints are represented in terms of line overload and steady state stability margin. And the reliability criterion is dealt with the suppression of failure cost and with single-contingency analysis. In general, the transmission planning problem requires integer solutions and its objective function is nonlinear. In this paper the objective function is defined as a sum of the present values of construction cost and the minimum operating cost of power system. The latter is represented as a sum of generation cost and failure cost considering the change of yearly load, economic dispatch, and the line contingency. For the calculation of operating cost linear programming is adopted on the base of DC load flow calculation, and for the optimization of main objective function nonlinear Branch-and-Bound algorithm is used. Finally, for improving the efficiency of B & B algorithm a new sensitivity analysis algorithm is proposed.

A Dual-Population Memetic Algorithm for Minimizing Total Cost of Multi-Mode Resource-Constrained Project Scheduling

  • Chen, Zhi-Jie;Chyu, Chiuh-Cheng
    • Industrial Engineering and Management Systems
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    • v.9 no.2
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    • pp.70-79
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    • 2010
  • Makespan and cost minimization are two important factors in project investment. This paper considers a multi-mode resource-constrained project scheduling problem with the objective of minimizing costs, subject to a deadline constraint. A number of studies have focused on minimizing makespan or resource availability cost with a specified deadline. This problem assumes a fixed cost for the availability of each renewable resource per period, and the project cost to be minimized is the sum of the variable cost associated with the execution mode of each activity. The presented memetic algorithm (MA) consists of three features: (1) a truncated branch and bound heuristic that serves as effective preprocessing in forming the initial population; (2) a strategy that maintains two populations, which respectively store deadline-feasible and infeasible solutions, enabling the MA to explore quality solutions in a broader resource-feasible space; (3) a repair-and-improvement local search scheme that refines each offspring and updates the two populations. The MA is tested via ProGen generated instances with problem sizes of 18, 20, and 30. The experimental results indicate that the MA performs exceptionally well in both effectiveness and efficiency using the optimal solutions or the current best solutions for the comparison standard.

Simulation of Vehicle-Structure Dynamic Interaction by Displacement Constraint Equations and Stabilized Penalty Method (변위제한조건식과 안정화된 Penalty방법에 의한 차량 주행에 따른 구조물의 동적상호작용 해석기법)

  • Chung, Keun Young;Lee, Sung Uk;Min, Kyung Ju
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.4D
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    • pp.671-678
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    • 2006
  • In this study, to describe vehicle-structure dynamic interaction phenomena with 1/4 vehicle model, nonlinear Hertzian contact spring and nonlinear contact damper are adopted. The external loads acting on 1/4 vehicle model are selfweight of vehicle and geometry information of running surface. The constraint equation on contact surface is implemented by the Penalty method with stabilization and the reaction from constraint violation. To describe pitching motion of various vehicles two types of the displacement constraint equations are exerted to connect between car bodies and between bogie frames, i.e., the rigid body connection and the rigid body connection with pin, respectively. For the time integration of dynamic equations of vehicles and structure Newmark time integration scheme is adopted. To reduce the error caused by inadequate time step size, adaptive time-stepping technique is also adopted. Thus, it is expected that more versatile dynamic interaction phenomena can be described by this approach and it can be applied to various railway dynamic problems with low computational cost.