• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제17권4호
• /
• pp.1100-1122
• /
• 2023

Scheduling user-submitted cloud tasks to the appropriate virtual machine (VM) in cloud computing is critical for cloud providers. However, as the demand for cloud resources from user tasks continues to grow, current evolutionary algorithms (EAs) cannot satisfy the optimal solution of large-scale cloud task scheduling problems. In this paper, we first construct a large- scale multi-objective cloud task problem considering the time and cost functions. Second, a multi-objective optimization algorithm based on multi-factor optimization (MFO) is proposed to solve the established problem. This algorithm solves by decomposing the large-scale optimization problem into multiple optimization subproblems. This reduces the computational burden of the algorithm. Later, the introduction of the MFO strategy provides the algorithm with a parallel evolutionary paradigm for multiple subpopulations of implicit knowledge transfer. Finally, simulation experiments and comparisons are performed on a large-scale task scheduling test set on the CloudSim platform. Experimental results show that our algorithm can obtain the best scheduling solution while maintaining good results of the objective function compared with other optimization algorithms.

• 대한산업공학회지
• /
• 제20권3호
• /
• pp.105-116
• /
• 1994

This paper presents an inventory model with partial backorders for the situation in which demand is deterministic, lead time follows normal distribution and back order ratio during the stockout period varies in proportion to the length of backorder period In this situations, an objective function is formulated to minimize a time-proportional backorder cast and a fixed penalty cost per unit lost. And then the procedure of iterative solution method for the model is developed to find optimal reorder paint and order quantity and a numerical example to illustrate the proposed method is presented.

• 한국전산구조공학회:학술대회논문집
• /
• 한국전산구조공학회 1993년도 가을 학술발표회논문집
• /
• pp.106-112
• /
• 1993

This paper presents the optimum design of reinforced concrete conical shell which is fixed at the base and free at the top. The calculation of stresses is done using the SMAP(Segmented Matrix Analysis Package)program which uses the simple finite element method of analysis. The objective function contains the ratios of the unit cost of reinforcements and formwork to that of concrete. To Simplify the optimization procedure, the final optimum design of conical shell is obtained by combining the result of each element. The results are presented and discussed.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
• /
• pp.240-245
• /
• 1990

A on-line optimization scheme based on model in a binary distillation process is proposed. A reduced-order model utilized the concept of collocation is used as a process model and the recursive prediction error method is employed to identify the reduced-order model. The concentrations of end products are controlled by nonlinear adaptive predictive control algorithm. The objective function is constructed to find optimum operate condition for saving utility cost. The proposed optimization is scheme is tested through simulation studies in 13-staged water-methanol distillation column.

• 대한전기학회논문지
• /
• 제38권8호
• /
• pp.585-592
• /
• 1989

This paper presents an efficient algorithm for the reactive planning of transmission network under normal operating conditions. The optimal operation of a power system is a prerequisite to obtain the optimal investment planning. The operation problem is decomposed into a P-optimization module and a Q-optimization module, but both modules use the same objective function of generation cost. In the investment problem, a new variable decomposition technique is adopted which can operate the operation and the investment variables. The optimization problem is solved by using the gradient projection method (GPM).

• 대한안전경영과학회:학술대회논문집
• /
• 대한안전경영과학회 2005년도 춘계학술대회
• /
• pp.171-175
• /
• 2005

본 연구에서는 ABC(Activity-Based Costing),활동기준원가를 설명하고, 한 업체를 대상으로 Cost structure를 파악하여,$Z_{abc}$ (ABC=based objective function value)를 최대화 하는 값을 찾아 이익을 최대화 시켜 기업가치를 향상시키고자 모형을 설계한다. 이를 위해 변수를 결정하고, 제약을 설정하게 된다. 이를 통해 수학적 모형을 완성 시뮬레이션을 통한 이익을 최대화 시키는 활동원가의 활동들을 규명한다.

• 산업경영시스템학회지
• /
• 제18권36호
• /
• pp.93-103
• /
• 1995

This paper des with an economic production quantity model with partial backorders for the situation in which production lead time is deterministic and demand during lead time follows a continuous distribution. In the model, an objective function is formulated In minimize an average annual inventory cost. And then the procedure of iterative solution method for the model is developed to find both production reorder point and production quantity. Finally, sensitivity analysis for various partial backorder ratios and standard deviations of demand during production lead time are presented.

• 한국전산구조공학회:학술대회논문집
• /
• 한국전산구조공학회 1998년도 봄 학술발표회 논문집
• /
• pp.262-271
• /
• 1998

Recent, more and more steel deck bridges are adopted for the design of long span bridges and the upgrading of existing concrete deck bridges, mainly because of reduced self weight, higher stiffness and efficient erection compared to concrete decks. The main objective of this study is to propose on formulation of the design optimizations to develop an optimal desist program required for optimum desist for orthotropic steel-deck bridges. The objective function of the optimization is formulated as a minimum initial cost design problem. The behavior and design constraints are formulated based on the ASD and LRFD criteria of the Korean Bridge Design Code(1996). The optimum design program developed in this study consists of two steps. In the first step the system optimization of the steel box girder bridges is carried out. And in the second step the program provided the optimum design of the orthotropic steel-deck with close ribs. In the optimal design program the analysis module for the deck optimization is based on the Pelican Esslinger method. The optimizer module of the program utilizes the ADS(Automated Desist Synthesis) routines using the optimization techniques fuor constrained optimization. From the results of real application examples, The cost effectiveness of optimum orthotropic steel-deck bridges designs based on both ASD and LRFD methods is investigated by comparing the results with those of conventional designs, and it may be concluded that the design developed in this study seems efficient and robust for the optimization of orthotropic steel-deck bridges

• Smart Structures and Systems
• /
• 제31권3호
• /
• pp.247-257
• /
• 2023

In structural health monitoring of large-scale structures, optimal sensor placement plays an important role because of the high cost of sensors and their supporting instruments, as well as the burden of data transmission and storage. In this study, a vibration sensor placement algorithm based on deep reinforcement learning (DRL) is proposed, which can effectively solve non-convex, high-dimensional, and discrete combinatorial sensor placement optimization problems. An objective function is constructed to estimate the quality of a specific vibration sensor placement scheme according to the modal assurance criterion (MAC). Using this objective function, a DRL-based algorithm is presented to determine the optimal vibration sensor placement scheme. Subsequently, we transform the sensor optimal placement process into a Markov decision process and employ a DRL-based optimization algorithm to maximize the objective function for optimal sensor placement. To illustrate the applicability of the proposed method, two examples are presented: a 10-story braced frame and a sea-crossing bridge model. A comparison study is also performed with a genetic algorithm and particle swarm algorithm. The proposed DRL-based algorithm can effectively solve the discrete combinatorial optimization problem for vibration sensor placements and can produce superior performance compared with the other two existing methods.

• Advances in Energy Research
• /
• 제6권1호
• /
• pp.55-73
• /
• 2019

The cost incurred by voltage sag effect in power networks has always been of important concern for discussions. Due to the environmental constraints, fossil fuel shortage crisis and low efficiency of conventional power plants, decentralized generation and renewable based DG have become trends in recent decades; because DGs can reduce the voltage sag effect in distribution networks noticeably; therefore, optimum allocation of DGs in order to maximize their effectiveness is highly important in order to maximize their effectiveness. In this paper, a new method is proposed for calculating the cost incurred by voltage sag effect in power networks. Thus, a new objective function is provided that comprehends technical standards as minimization of the cost incurred by voltage sag effect, active power losses and economic criterion as the installation and maintenance costs of DGs. Considering operational constraints of the system, the optimum allocation of DGs is a constrained optimization problem in which Lightning Attachment procedure optimization (LAPO) is used to resolve it and is the optimum number, size and location of DGs are determined in IEEE 33 bus test system and IEEE 34 bus test system. The results show that optimum allocation of DGs not only reduces the cost incurred by voltage sag effect, but also improves the other characteristics of the system.