• International Journal of Control, Automation, and Systems
• /
• 제4권5호
• /
• pp.601-614
• /
• 2006

In this paper, a study on task assignment strategies for a complex real-time network system is presented. Firstly, two task assignment strategies are proposed to improve previous strategies. The proposed strategies assign tasks with meeting end-to-end real-time constraints, and also with optimizing system utilization through period modulation of the tasks. Consequently, the strategies aim at the optimizationto optimize of system performance with while still meeting real-time constraints. The proposed task assignment strategies are devised using the genetic algorithmswith heuristic real-time constraints in the generation of new populations. The strategies are differentiated by the optimization method of the two objectives-meeting end-to-end real-time constraints and optimizing system utilization: the first one has sequential genetic algorithm routines for the objectives, and the second one has one multiple objective genetic algorithm routine to find a Pareto solution. Secondly, the performances of the proposed strategies and a well-known existing task assignment strategy using the BnB(Branch and Bound) optimization are compared with one other through some simulation tests. Through the comparison of the simulation results, the most adequate task assignment strategies are proposed for some as system requirements-: the optimization of system utilization, the maximization of running tasktasks, and the minimization of the number of network node nodesnumber for a network system.

• 한국전산구조공학회:학술대회논문집
• /
• 한국전산구조공학회 2006년도 정기 학술대회 논문집
• /
• pp.451-458
• /
• 2006

The goal of many researchers in the field of structural engineering is to reduce both damage to building structures and discomfort of their inhabitants during strong motion seismic events. The present paper reports on analytical work conducted with this aim in mind as a prior research of experimental study. A four-story, 6.4 m tall, laboratory model of a building is employed as a example structure. The laboratory structure has graphite epoxy columns and each floor is equipped with a chevron brace that serves to resist inter-story drift with the installation of a magnetorheological (MR) damper. An artificial excitation has been generated with a robust range of seismic characteristics. A series of numerical simulations demonstrates that an optimized fuzzy controller is capable of robust performance for a variety of seismic base motions. Optimization of the fuzzy controller is achieved using multi-objective genetic algorithm(MOGA), i.e. NSGA-II. Multiple objective functions are used in order to reduce both peak and root-means-squared displacement and accelerations at the floor levels of the building.

• Smart Structures and Systems
• /
• 제26권5호
• /
• pp.545-558
• /
• 2020

A design method of a Multiple Tuned Mass Damper (MTMD) system is presented for wind induced vibration control of a cable-supported roof structure. Modal contribution analysis is carried out to determine the dominating modes of the structure for the MTMD design. Two MTMD systems are developed for two most dominating modes. Each MTMD system is composed of multiple TMDs with small masses spread at multiple locations with large responses in the corresponding mode. Frequencies of TMDs are distributed uniformly within a range around the dominating frequencies of the roof structure to enhance the robustness of the MTMD system against uncertainties of structural frequencies. Parameter optimizations are carried out by minimizing objective functions regarding the structural responses, TMD strokes, robustness and mass cost. Two optimization approaches are used: Single Objective Approach (SOA) using Sequential Quadratic Programming (SQP) with multi-start method and Multi-Objective Approach (MOA) using Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The computation efficiency of the MOA is found to be superior to the SOA with consistent optimization results. A Pareto optimal front is obtained regarding the control performance and the total weight of the TMDs, from which several specific design options are proposed. The final design may be selected based on the Pareto optimal front and other engineering factors.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
• /
• 제51권5호
• /
• pp.234-241
• /
• 2002

An optical pickup actuator is an objective-lens-moving mechanism that provides a means to follow the disk displacement accurately(1). In this paper, a slim type optical pickup actuator for Notebook PCs is analyzed and designed to improve the driving sensitivity A three dimensional equivalent magnetic circuit network method (3D-EMCN method) is proposed for an analysis method which provides better characteristics in both precision and computation time of analysis comparing with a commercial three-dimensional finite element (3D-FEM) codes. To verify the validity of proposed method, we made a comparison between the analysis results and the experimental ones. We also compared this analysis results with 3D-FEM results. Among the several optimal algorithm, we adopt a niching genetic algorithm, which renders a set of the multiple optimal solutions. RCS (Restricted Competition Selection) niching genetic algorithm is used for optimal design of the actuator's performance. Recently, the pickup actuator needs additional driving structure for radial and tangential tilting motion to obtain better pick-up performance. So we applied the proposed method to the model containing tilting coils.

• Industrial Engineering and Management Systems
• /
• 제11권4호
• /
• pp.310-330
• /
• 2012

Scheduling is an important tool for a manufacturing system, where it can have a major impact on the productivity of a production process. In manufacturing systems, the purpose of scheduling is to minimize the production time and costs, by assigning a production facility when to make, with which staff, and on which equipment. Production scheduling aims to maximize the efficiency of the operation and reduce the costs. In order to find an optimal solution to manufacturing scheduling problems, it attempts to solve complex combinatorial optimization problems. Unfortunately, most of them fall into the class of NP-hard combinatorial problems. Genetic algorithm (GA) is one of the generic population-based metaheuristic optimization algorithms and the best one for finding a satisfactory solution in an acceptable time for the NP-hard scheduling problems. GA is the most popular type of evolutionary algorithm. In this survey paper, we address firstly multiobjective hybrid GA combined with adaptive fuzzy logic controller which gives fitness assignment mechanism and performance measures for solving multiple objective optimization problems, and four crucial issues in the manufacturing scheduling including a mathematical model, GA-based solution method and case study in flexible job-shop scheduling problem (fJSP), automatic guided vehicle (AGV) dispatching models in flexible manufacturing system (FMS) combined with priority-based GA, recent advanced planning and scheduling (APS) models and integrated systems for manufacturing.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제6권10호
• /
• pp.2509-2528
• /
• 2012

Time division multiple access (TDMA) is a widely used media access control (MAC) technique that can provide collision-free and reliable communications, save energy and bound the delay of packets. In TDMA, energy saving is usually achieved by switching the nodes' radio off when such nodes are not engaged. However, the frequent switching of the radio's state not only wastes energy, but also increases end-to-end delay. To achieve high energy efficiency and low delay, as well as to further minimize the number of time slots, a multi-objective TDMA scheduling problem for industrial wireless mesh networks is presented. A hybrid algorithm that combines genetic algorithm (GA) and simulated annealing (SA) algorithm is then proposed to solve the TDMA scheduling problem effectively. A number of critical techniques are also adopted to reduce energy consumption and to shorten end-to-end delay further. Simulation results with different kinds of networks demonstrate that the proposed algorithm outperforms traditional scheduling algorithms in terms of addressing the problems of energy consumption and end-to-end delay, thus satisfying the demands of industrial wireless mesh networks.

• Structural Engineering and Mechanics
• /
• 제43권6호
• /
• pp.795-821
• /
• 2012

The size and topology of geometrically nonlinear dome structures are optimized thereby minimizing both its entire weight & joint (node) displacements and maximizing load-carrying capacity. Design constraints are implemented from provisions of American Petroleum Institute specification (API RP2A-LRFD). In accordance with the proposed design constraints, the member responses computed by use of arc-length technique as a nonlinear structural analysis method are checked at each load increment. Thus, a penalization process utilized for inclusion of unfeasible designations to genetic search is correspondingly neglected. In order to solve this complex design optimization problem with multiple objective functions, Non-dominated Sorting Genetic Algorithm II (NSGA II) approach is employed as a multi-objective optimization tool. Furthermore, the flexibility of proposed optimization is enhanced thereby integrating an automatic dome generating tool. Thus, it is possible to generate three distinct sphere-shaped dome configurations with varying topologies. It is demonstrated that the inclusion of brace (diagonal) members into the geometrical configuration of dome structure provides a weight-saving dome designation with higher load-carrying capacity. The proposed optimization approach is recommended for the design optimization of geometrically nonlinear dome structures.

• 경영과학
• /
• 제17권2호
• /
• pp.55-65
• /
• 2000

This paper addresses a problem of machining route selection in multi-stage process with machine group. This problem is considered the subcontracting and the production in-house such as regular and overtime work. the proposed model is formulated as a 0-1 integer programming constraining the avaliable time of each machine for planning period and total overtimes. The objective of the model is to minimize the sum of processing cost, overtime cost, and subcontracting cost. To solve this model, a genetic algorithm(GA) approach is developed. The effectiveness of the proposed GA approach is evaluated through comparisons with the optimal solution obtained from the branch and bound. In results, the same optimal solution is obtained from two methods at small size problem, and the consistent solution is provided by the GA approach at large size problem. The advantage of the GA approach is the flexibility into decision-making process because of providing multiple machining routes.

• 산업경영시스템학회지
• /
• 제23권54호
• /
• pp.13-26
• /
• 2000

Machining route selection to produce parts should be based on shop flow information because of input data at scheduling tasks and is one of the main problem in process planning. This paper addresses the problem of machining route selection in multi-stage process with machine group included a similar function. The model proposed is formulated as 0-1 integer programing considering the relation of parts and machine table size, avaliable time of each machine for planning period, and delivery date. The objective of the model is to minimize the sum of processing, transportation, and setup time for all parts. Genetic algorithm approach is developed to solve this model. The efficiency of the approach is examined in comparison with the method of branch and bound technique for the same problem. Also, this paper is to solve large problem scale and provide it if the multiple machining routes are existed an optimal solution.

• Earthquakes and Structures
• /
• 제23권1호
• /
• pp.1-11
• /
• 2022

This study implements a hybrid Genetic Algorithm to detect, locate, and quantify structural damage for multistory shear buildings using partial modal data. Measuring modal responses at multiple locations on a structure is both challenging and expensive in practice. The proposed method's objective function is based on the building's dynamic properties and can also be employed with partial modal information. This method includes initial residuals between the numerical and experimental model and a damage penalization term to avoid false damages. To test the proposed method, a numerical example of a ten-story shear building with noisy and partial modal information was explored. The obtained results were in agreement with the previously published research. The proposed method's performance was also verified using experimental modal data of an 8-DOF spring-mass system and a five-story shear building. The predicted results for numerical and experimental examples indicated that the proposed method is reliable in identifying the damage for multistory shear buildings.