• International journal of advanced smart convergence
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• v.9 no.2
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• pp.157-163
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• 2020

Recently the blockchain technology has been actively studied due to its great potentiality. The smart contract is a key mechanism of the blockchain system. Due to the short history of the smart contract, many issues have not been solved yet. One main issue is vulnerability and another main issue is cost optimization. While the vulnerability of smart contract has been actively studied, the cost optimization has been rarely studied. In this paper, we propose two cost optimization methods for smart contracts running on the blockchain system. Triggering a function in a smart contract program code may require costs and it is repeated continuously. So the minimization of costs required to trigger a function of smart contract while maintaining the performance equally is very important. The proposed two methods minimize the usage of expensive permanent variables deployed on the blockchain system. We apply the proposed two methods to three prevalent blockchain platforms: Ethereum, Klaytn and Tron. Evaluation experiments verify that the proposed scheme significantly reduces the costs of functions in the smart contract written with Solidity.

• Journal of the Korea Safety Management & Science
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• v.8 no.3
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• pp.125-141
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• 2006

If do not become whole optimization because enterprise's individual enterprise internal determinate improvement effort is associated with activity in enterprise SCM, competitive power can not but be extremely limited the result. Therefore, to spur in hidden cost's discovery and logistics' optimization is actuality. In this paper, as long as it is by logistics cost except empty driving if reverse logistics happens in distribution channel progressing, logistics reverse logistics' hidden cost through model that do minimization profit of logistics to look for plan that can do maximization try. Finally, is based on dual of distribution cost and profit of logistics and reverse logistics and achieves Pull, optimal system modeling that use Push system and gropes method of effective logistics cost.

• Journal of Distribution Science
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• v.15 no.2
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• pp.15-20
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• 2017

Purpose - This paper aims to suggest a delivery constrained internet shopping optimization problem (DISOP) which must be solved for online recommendation system to provide a customized service considering cost and delivery conditions at the same time. Research design, data, and methodology - To solve a (DISOP), we propose a multi-objective formulation and a solution approach. By using a commercial optimization software (LINDO), a (DISOP) can be solved iteratively and a pareto optimal set can be calculated for real-sized problem. Results - We propose a new research problem which is different with internet shopping optimization problem since our problem considers not only the purchasing cost but also delivery conditions at the same time. Furthermore, we suggest a multi-objective mathematical formulation for our research problem and provide a solution approach to get a pareto optimal set by using numerical example. Conclusions - This paper proposes a multi-objective optimization problem to solve internet shopping optimization problem with delivery constraint and a solution approach to get a pareto optimal set. The results of research will contribute to develop a customized comparison and recommendation system to help more easy and smart online shopping service.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.659-668
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• 2018

This paper proposes an optimization approach of a grid-connected photovoltaic and wind hybrid energy system including energy storage considering voltage fluctuation in the electricity grid. A techno-economic analysis is carried out in order to minimize the size of hybrid system by considering the benefit-cost. Lithium-ion battery type is used for both managing the electricity selling to the grid and reducing voltage fluctuation. A new technique is developed to limit the voltage perturbation caused by the solar irradiance and the wind speed through determining the state-of-charge of battery for every hour of a day. Improved particle swarm optimization (PSO) methods, referred to as FC-VACPSO which combines Fast Convergence Particle Swarm Optimization (FCPSO) method and Variable Acceleration Coefficient Based Particle Swarm Optimization (VACPSO) method are used to solve the optimization problem. A comparative study has been performed between standard PSO method and PSO based methods to extract the best size with the benefit cost. A sensitivity analysis has been studied for different kinds and costs of batteries, by considering variable and constant state-ofcharge of battery. The simulations, performed under Matlab environment, yield good results using the FC-VACPSO method regarding the convergence and the benefit cost of the hybrid system.

• Journal of Biosystems Engineering
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• v.7 no.1
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• pp.42-52
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• 1982

This study was intended to develop a cost function for the natural air in-bin drying: system which could lead to an optimization of the drying system cost. Based on the cost function developed, a series of simulated drying tests were conducted with 10-year weather data (1970~1979) for 7 different regions by applying an appropriate levels of system factors. System performance factors treated in this study were initial moisture content, airflow rate, bin diameter and grain depth. An optimization procedure to find the least cost system was developed as follows: First, the worst year of the past decade was determined in consideration of the dryiang time and maximum dry matter loss. Second, the minimum airflow rate for a fixed bin diameter and grain depth was determined. Third, the optimum grain depth was found for the minimum airflow rate with different initial moisture contents and bin diameters. The results obtained in this study are summarized as follows: 1. The optimization procedure developed in this study was able to reduce the time and efforts significantly. 2. Optimum values of drying parameters including airflow rate, grain depth, and fan size were determined for different initial moisture contents and bin diameters in each region. The results are shown in Tables 3 to 9. 3. Optimum grain depths decreased as the initial moisture content and airflow rate increased. 4. Drying time for the least cost system should be reduced with higher initial moisture content and lower drying potential to prevent grain spoilage. 5. The fixed cost was 65 to 75 percent of the total system cost and the variable cost was 25 to 35 percent. To reduce the fixed cost it is desirable to use a drying bin 2 or 3 times a year.

• Earthquakes and Structures
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• v.7 no.3
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• pp.271-294
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• 2014

In recent years, along with the advances made in performance-based design optimization, the need for fast calculation of response parameters in dynamic analysis procedures has become an important issue. The main problem in this field is the extremely high computational demand of time-history analyses which may convert the solution algorithm to illogical ones. Two simplifying strategies have shown to be very effective in tackling this problem; first, simplified nonlinear modeling investigating minimum level of structural modeling sophistication, second, wavelet analysis of earthquake records decreasing the number of acceleration points involved in time-history loading. In this paper, we try to develop an efficient framework, using both strategies, to solve the performance-based multi-objective optimal design problem considering the initial cost and the seismic damage cost of steel moment-frame structures. The non-dominated sorting genetic algorithm (NSGA-II) is employed as the optimization algorithm to search the Pareto optimal solutions. The constraints of the optimization problem are considered in accordance with Federal Emergency Management Agency (FEMA) recommended design specifications. The results from numerical application of the proposed framework demonstrate the capabilities of the framework in solving the present multi-objective optimization problem.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.243-251
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• 2013

Cash management is a major concern for all contractors in the construction industry. It is arguable that cash is the most critical resource of all. A contractor needs to secure sufficient funds to navigate the project to the end, while keeping an eye on maximizing profits along the way. Past research attempted to address such topic via developing models to tackle the time-cost tradeoff problem, cash flow forecasting, and cash flow management. Yet, little was done to integrate the three aspects of cash management together. This paper, as such, presents a comprehensive model that integrates the time-cost tradeoff problem, cash flow management, and cash flow forecasting. First, the model determines the project optimal completion time by considering the different alternative construction methods available for executing project activities. Second, it investigates different funding alternatives and proposes a project-level cash management plan. Two funding alternatives are considered; they are borrowing and company own financing. The model was built as a combinatorial optimization model that utilizes ant colony search capabilities. The model also utilizes Microsoft Project software and spreadsheets to maintain an environment that incorporates activities, their durations, and other project data, in order to estimate project completion time and cost. Ant Colony Optimization algorithm was coded as a Macro program using VBA. Finally, an example project was used to test the developed model, where it acted reliably in maximizing the contractor's profit in the test project.

• Journal of Ocean Engineering and Technology
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• v.23 no.1
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• pp.1-6
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• 2009

The paper describes results of a sensitivity study on an optimum mooring cost as a function of safety factor and allowable maximum offset of the offshore floating structure by finding the anchor leg component size and the declination angle. A harmony search (HS) based mooring optimization program was developed to conduct the study. This mooring optimization model was integrated with a frequency-domain global motion analysis program to assess both cost and design constraints of the mooring system. To find a trend of anchor leg system cost for the proposed sensitivity study, optimum costs after a certain number of improvisation were found and compared. For a case study a turret-moored FPSO with 3 ${\times}$ 3 anchor leg system was considered. To better guide search for the optimum cost, three different penalty functions were applied. The results show that the presented HS-based cost-optimum offshore mooring design tool can be used to find optimum mooring design values such as declination angle and horizontal end point separation as well as a cost-optimum mooring system in case either the allowable maximum offset or factor of safety varies.

• Structural Engineering and Mechanics
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• v.43 no.1
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• pp.31-51
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• 2012

This paper presents a computational study that explores the design of rigid steel frames by considering construction related costs. More specifically, two different aspects are investigated in this study focusing on the effects of (a) reducing the number of labor intensive rigid connections within a frame of given geometric layout, and (b) reducing the number of different member section types used in the frame. A genetic algorithm based optimization framework searches design space for these objectives. Unlike some studies that express connection cost as a factor of the entire frame weight, here connections and their associated cost factors are explicitly represented at the member level to evaluate the cost of connections associated with each beam. In addition, because variety in member section types can drive up construction related costs, its effects are evaluated implicitly by generating curves that show the trade off between cost and different numbers of section types used within the frame. Our results show that designs in which all connections are considered to be rigid can be excessively conservative: rigid connections can often be eliminated without any appreciable increase in frame weight, resulting in a reduction in overall cost. Eliminating additional rigid connections leads to further reductions in cost, even as frame weight increases, up to a certain point. These complex relationships between overall cost, rigid connections, and member section types are presented for a representative five-story steel frame.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3030-3049
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• 2023

With the development and wide application of hybrid network computing modes like cloud computing, edge computing and fog computing, the customer service requests and the collaborative optimization of various computing resources face huge challenges. Considering the characteristics of network environment resources, the optimized deployment of service resources is a feasible solution. So, in this paper, the optimal goals for deploying service resources are customer experience and service cost. The focus is on the system impact of deploying services on load, fault tolerance, service cost, and quality of service (QoS). Therefore, the alternate node filtering algorithm (ANF) and the adjustment factor of cost matrix are proposed in this paper to enhance the system service performance without changing the minimum total service cost, and corresponding theoretical proof has been provided. In addition, for improving the fault tolerance of system, the alternate node preference factor and algorithm (ANP) are presented, which can effectively reduce the probability of data copy loss, based on which an improved cost-efficient replica deployment strategy named ICERD is given. Finally, by simulating the random occurrence of cloud node failures in the experiments and comparing the ICERD strategy with representative strategies, it has been validated that the ICERD strategy proposed in this paper not only effectively reduces customer access latency, meets customers' QoS requests, and improves system service quality, but also maintains the load balancing of the entire system, reduces service cost, enhances system fault tolerance, which further confirm the effectiveness and reliability of the ICERD strategy.