Time-cost Model Research Articles

Optimization of reliability centered predictive maintenance scheme for inertial navigation system

The goal of this study is to propose a reliability centered predictive maintenance scheme for a complex structure Inertial Navigation System (INS) with several redundant components. GO Methodology is applied to build the INS reliability analysis model—GO chart. Components Remaining Useful Life (RUL) and system reliability are updated dynamically based on the combination of components lifetime distribution function, stress samples, and the system GO chart. Considering the redundant design in INS, maintenance time is based not only on components RUL, but also (and mainly) on the timing of when system reliability fails to meet the set threshold. The definition of components maintenance priority balances three factors: components importance to system, risk degree, and detection difficulty. Maintenance Priority Number (MPN) is introduced, which may provide quantitative maintenance priority results for all components. A maintenance unit time cost model is built based on components MPN, components RUL predictive model and maintenance intervals for the optimization of maintenance scope. The proposed scheme can be applied to serve as the reference for INS maintenance. Finally, three numerical examples prove the proposed predictive maintenance scheme is feasible and effective.

Dynamic Optimization of Project Schedule Based on Life-Cycle Economic Benefits

There is a relationship of unity of opposites between the construction and operation period of the project.When the construction period of the project is shorten and the project is put into production in advance, income of operation period will be increased, at the same time, it will cause the increase of construction cost.Combining time-cost optimization with the financial evaluation of the project, from the perspective of the owner, on the basis of considering the capital time-value and the impact of large equipment replacement on the income of operation period, time-cost dynamic optimization model which maximize the project life-cycle net present value and is proved to be necessary and feasible through the case is established.

Uncertain random time-cost trade-off problem

Since for most projects, ‘new’ parts (with little or no historical data) and ‘old’ parts (with sufficient historical data) always coexist in the same project, uncertainty and randomness should be considered simultaneously in time-cost trade-off problem. In this paper, combined with uncertainty theory and dependent-chance programming, an uncertain random time-cost trade-off model is built. A crisp equivalent model is also given for some special case. Besides, uncertain random simulation and genetic algorithm are integrated for solving the proposed model.

Applicability of Bromilow´s Time-cost Model for Residential Projects in Slovakia

Abstract The concept of construction time has been mentioned by most researchers as one of the key factors of a successful project. Time-cost model for rapid estimation of construction time appeared in the world some fifty years ago and the most mentioned is model developed by Bromilow. The purpose of submitted research is to validate Bromilow´s time-cost (BTC) model and identify constants in BTC model in context with residential construction projects in Slovak construction conditions. The data for the study were obtained from 28 residential projects completed within the period 2010-2013 in regions of Slovakia. The data were analyzed using classical correlation and regression analysis

Development of Time-Cost Models for Building Construction Projects in Bangladesh

Estimating time and cost is an important mission in the early phase of a construction project, especially in feasibility study. It provides a foundation for making decision whether or not the project is performed on schedule and within budget. Thus, reliability of this estimate plays a key role in measuring the success of a project. This study was carried out to investigate the time-cost relationship in building construction projects in Bangladesh. The mathematical equation used in this study is based on Bromilow's equation. The research data were collected from sixty-three completed building projects through questionnaire survey. Type of clients, type of projects, and tender methods are the project characteristics considered in this study. The results of analysis indicated that the Bromilow's time-cost (BTC) models developed for each project characteristic are appropriate due to quite high coefficient of determination and relatively small mean percent errors. Among them, the forecasted model for time and cost according to tender methods is the best fit model. It is concluded that the BTC model could be applied in building construction project to predict its time and cost in Bangladesh. Four different regression models were also developed in this study. The results of BTC model between some selected countries were compared to gain the comprehensive view.

MRScheduling: An Effective Technique for Multi-Tenant Meeting Deadline in MapReduce

The multi-tenant jobs scheduling problem based on MapReduce framework has become more and more significant in contemporary society. Existing scheduling approach or algorithm no longer fit well in scenario that numerous jobs were submitted by multiple users at the same time. Therefore, taken enlarging jobs’ throughput for MapReduce into account, we firstly propose an MRScheduling which focuses on meeting job’s respective deadline. Considering the various parameters which are related to job execution time of a MapReduce’s job, we present a simply time-cost model, for the aim that quantifying the number of job’s assigned map slots and reduce slots. Then, an MRScheduling algorithm is discussed in details. Finally, we perform our approach on both real data and synthetic data on real distributed cluster to verify its effectiveness and efficiency.

A second life: Recycling production waste during the Middle Palaeolithic in layer L at Grotta del Cavallo (Lecce, Southeast Italy)

This paper presents the modalities of recycling in lithic assemblage in layer L at Grotta del Cavallo (Middle Palaeolithic, Southeast Italy). The layer exhibits a high diversity of exogenous (>50 km) and local (<5 Km) raw material, including marine shells for producing retouched tools. Recycling is attested in local raw material and in shell valves. I identified four recycling modalities, related to four object categories, and analysed each one separately: lithic retouched tools, macro tools, short products with sharp edges, and marine-shell tools with two orthogonal edges. I interpreted this behaviour in relation to a time-cost model. The aim was to evaluate the role of recycling in changing technological costs and to investigate if recycling was a planned strategy and how it was incorporated into the techno-economic organisation of the human group. The lithic assemblage displays a high spatio-temporal segmentation of productive sequences based on discoidal methods, the production of small flakes, the majority less than 3 cm in length, and a high technical investment in retouch. The results of the recycling cost-benefit analysis suggest that this behaviour was integrated into an economic setting regulated by time constrictions during tasks performed at the site within a logistic mobility. In this layer, recycling was an occasional behaviour, which allowed humans to respond to unplanned needs, and was facilitated by the low degree of volumetric constraints in the productive methods applied and by the short dimensions of the tools used. Recycling was an element that contributed to define the cultural entity, appearing as a specific trait in a given human group.

Role of Statistics and Engineering Judgment in Developing Optimized Time-Cost Relationship Models

AbstractWhen estimating the duration of the construction stage during the design stages of construction projects, empirical models are often used as a substitute for more accurate estimates based on detailed scheduling. These models, traditionally designated as time-cost relationships (TCR), derive from regressions relating the duration of concluded construction projects with characteristics that can be easily foreseen during the planning and design stages—both quantitative (e.g., cost, gross floor area, number of floors) and qualitative (e.g., type of contract). This paper reviews the approaches that have been adopted to develop the TCR models and discusses the complementary roles that statistics and engineering judgment can play towards their optimization and enhanced accuracy. This discussion includes the statistical and practical implications of (1) the quantitative independent variables used, (2) the qualitative independent variables used, and (3) the mathematical structure used. The paper aims at de...

A novel energy-efficient resource allocation algorithm based on immune clonal optimization for green cloud computing

Abstract Cloud computing is a style of computing in which dynamically scalable and other virtualized resources are provided as a service over the Internet. The energy consumption and makespan associated with the resources allocated should be taken into account. This paper proposes an improved clonal selection algorithm based on time cost and energy consumption models in cloud computing environment. We have analyzed the performance of our approach using the CloudSim toolkit. The experimental results show that our approach has immense potential as it offers significant improvement in the aspects of response time and makespan, demonstrates high potential for the improvement in energy efficiency of the data center, and can effectively meet the service level agreement requested by the users.

Logistics Cost Optimization in Total Life Cycle of Power Grid Engineering Project Using Improved Ant Colony Algorithm

Effective control of the logistics costs of the power grid engineering cost project can minimize the total cost, and improve the economic efficiency of it. This paper regards the minimal logistics cost of the power grid engineering cost project in the total life cycle as goal, and puts forward the project logistics time-cost trade-off optimization model based on improved ant colony algorithm. This model integrates the two objectives of time and cost into a single objective in terms of adaptive weight approach, and this approach is applied to ant colony algorithm to search for solutions. The result of the case study indicates that this approach is very effective for determining practical solutions, and has strong global searching ability and efficiency. So the model is very suitable for solving the problem of power grid engineering cost project logistics cost optimization.

Joint production and shipment lot sizing for a delivery price-based production facility

A joint economic production quantity (EPQ) and delivery quantity model for a production system is investigated in this paper. More specifically, an EPQ policy is implemented in the production system, while a smaller shipping quantity is periodically dispatched to the customer. The production system is also responsible for the shipment cost, i.e. a delivery price-based procurement from the customer. The considered cost includes setup cost to launch the batch production, inventory carrying cost, and transportation cost, where the transportation cost is a function of the delivery quantity. A per unit time cost model is developed and analysed to determine the optimal production and delivery quantities. Under some mild conditions, it can be shown that the joint cost function is convex with respect to the production quantity; and the number of delivery is an integer in each replenishment cycle. Computational study has demonstrated the significant impact of the joint decision model on the operating cost. In particular, the reduction in total cost can be more than 15% when inventory carrying costs, and/or transportation costs, are high.

Do Tradeoff Models have what it Takes to Make a Real Tradeoff?

There is a growing body of knowledge on project tradeoff models; meanwhile, there are concerns about the models’ applicability. The contemporary research on tradeoffs is mainly based on the time-cost models in planning, which do not provide a proper basis for tradeoffs in other contexts. This paper is aimed at shedding some light on the theoretical and practical deficiencies of tradeoff models through comparison of their fundamentals with the results of other related studies. It highlights the deficiencies of current models and draws attention to the necessity of exploring the real problems’ characteristics and methods’ capabilities prior to model development.

China’s New Energy Passenger Vehicle Development Scenario Analysis Based on Life Time Cost Modelling

Based on the analysis on the development trend of vehicle technology, vehicle price, vehicle fuel economy and fuel supply price, the new energy vehicle (NEV) passenger car development scale is projected on different scenario with the application of life time cost model. Three scenarios are set to find electric vehicle (EV) and fuel cell vehicle (FCV) development potential in future to their pessimistic and optimistic assumptions in China. The results are demonstrated: 1) NEV development needs a long time due to high initial cost for vehicle buyer; 2) EV will develop quickly under if there is quick development of battery technology; and 3) FCV can only develop in a large scale in 20 - 30 years even in the optimistic scenario.

Time-Cost Optimization of Complex Clinical Trials

A number of studies have been published presenting simulation models of the patient recruitment process. Patient accrual may be viewed in the context of the key components of the trial: study start-up, enrollment, patient stratification, globalization, and so on. Whereas previous research has tended to focus on the mechanics of the simulation models, we have focused on the key components of a clinical study and how to model each of the components. We modeled study start-up and patient enrollment processes using cumulative normal distribution functions for study start-up and mean cumulative functions to model cumulative enrollment per active site. The cost function was specified in terms of project time, number of sites and number of patients. We showed how the resulting time-cost model may be influenced by central institutional review boards, patient stratification, and the global distribution of sites. The model was fit to actual study performance data incorporating these factors. Sensitivity analyses were used to explore trade-offs between project time and cost. Decision parameters included the number of sites, which regions of the world to include, the mix of sites by region of the world, the relative size of various patient strata, mean cumulative enrollment rates, and so on. Mean and variance of the time to complete study start-up was sharply reduced for the set of sites using central institutional review boards in an outpatient cardiovascular trial. Patient stratification tends to prolong the trial and reduce the overall mean cumulative enrollment rates per active site. Mean enrollment rates tend to decline as strata fill up that are simpler to recruit into, and the total project time is prolonged. Including sites in Eastern Europe, South America, and India may increase mean relative enrollment rates by as much as three times the US rate and reduce total project time accordingly. Adding sites may reduce project time while adding only marginally to costs, because reductions in time-based costs offset additions in site-based costs. Monte Carlo simulation of the model enables probability statements regarding study completion time. time-cost models that reflect the complexity and idiosyncrasies of specific trials are critical to prudent planning for individual trials and clinical development plans. Given the formidable challenges in attracting funding for novel drugs and devices, time-cost models have an important role to play in planning and managing global clinical trials.

Time–cost relationship of building projects: statistical adequacy of categorization with respect to project location

Construction duration is one of the key elements to determine the success of a project. Several models have been developed to provide precise predictions of construction duration. The datasets in previous studies comprise observations from particular countries. This precludes examination of the role of project location at the country level for modelling construction duration. The aim, therefore, is to test the statistical adequacy of categorizing projects with respect to their locations for modelling construction duration. A formal procedure to evaluate the adequacy of categorizing observations is also presented. It is intended to contribute to the epistemology of modelling construction duration. The dataset was generated from a global client. It contains information on 246 projects from 25 different countries. This creates a categorical variable for location. Bromilow’s time–cost model is chosen to assess the adequacy of this categorization. A full model with indicator and interaction variables is compared to a restricted one. Parameter estimation was performed according to the ordinary least squares method. F‐statistics are calculated and the probability of the value is significant. The results show that two distinct groups with substantial changes in model parameters exist in the dataset. It is also noted that conclusions are valid over the selected population.

Estimation of Time for Wenchuan Earthquake Reconstruction in China

Time is considered extremely urgent in China’s Wenchuan earthquake reconstruction. However, little research has been undertaken on estimating the time needed for reconstruction in China, especially for this specific reconstruction. Therefore, this paper aims to explore the time-cost relationship for the Wenchuan earthquake reconstruction. Both the Bromilow’s time-cost (BTC) model and the Elman network (EN) model have been developed to predict the time of Wenchuan earthquake reconstruction projects. Data have been obtained from 72 completed construction projects in the six cities that were seriously affected by the major Wenchuan earthquake. The result from the BTC model has been compared with that from the EN model to determine which one is more accurate. The results show that the EN model provides a more accurate time prediction for Wenchuan earthquake reconstruction than the BTC model does, though the BTC model is more suitable for application in practice. It is also shown that the proposed models are b...

Grid Independent Task Scheduling Multi-Objective Optimization Model and Genetic Algorithm

The characteristic of heterogeneous grid environment results in that the task scheduling is constrained by a number of factors such as the length of scheduling, the performance of security, and the cost of scheduling , etc. Firstly, under the consideration of the task scheduling demand for secure performance. A security benefit function and the corresponding time cost model are constructed. Secondly , according to the past behavior of grid resource nodes, a simple and efficient node’s credibility dynamic evaluation model is built by using the weighted function. Thirdly, b ased on these, a new constrained multi-objective grid task scheduling mode is proposed. In order to solve this model, the relationship between the characteristic of the task and the different performance among nodes is used to define the individual relationship matrix; then the subjection degree function is used to transform each relationship matrix into a fuzzy matrix . A ccording to the different effects of each objective in the final objective , each weight in the final decision-making is determined. By doing so, the multi-objective model is transformed into a single-objective model. Through the design of new crossover operator and an uniform mutation operator, a genetic algorithm called MUGA for the transformed problem is proposed. Finally, s imulation results show that the proposed algorithm is better than the compared ones in terms of the length of the task scheduling, security efficiency value, reliability and scheduling costs.

Time–cost optimization: using GA and fuzzy sets theory for uncertainties in cost

Uncertainties should be considered in any time–cost trade‐off problems when minimizing project cost and duration, which leads to the so‐called stochastic time–cost trade‐off problem. A new approach to investigate stochastic time–cost trade‐off problems employing fuzzy logic theory is presented. The proposed approach fully embeds the fuzzy structure of the uncertainties in total direct cost into the model. An appropriate GA is used to develop a solution to the multi‐objective fuzzy time cost model. The accepted risk level of the project manager is defined through α cut approach for which a separate Pareto front with set of non‐dominated solutions has been developed. To compare the alternative set of options for any assumed project duration, associated fuzzy costs for different values of α cut are ranked employing two appropriate approaches for fuzzy costs comparison. The proposed models are applied to solve two benchmark test problems. It is shown that the models facilitate the decision‐making process by selecting specified risk levels and employing the associated Pareto front.

Estimating Performance Time for Construction Projects

The prediction of performance time for construction projects is a problem of interest to both researchers and practitioners. This research seeks to gain insight into the significant factors impacting construction duration by developing a regression model. Data were collected for 856 facility projects completed between 1988 and 2004. These data were analyzed using Bromilow’s time-cost (BTC) model (1969) as well as multiple linear regression. The multiple linear regression model was found to provide the most acceptable prediction. As in the BTC model and previous research reported in the literature, a significant correlation was found to exist between cost and duration. However, several other factors were also identified that resulted in significantly lower than average construction durations. These include projects completed within certain management groupings, managed by a certain construction agent, and designed by in-house personnel.

Research on the fully fuzzy time-cost trade-off based on genetic algorithms

It is very difficult, to estimate exact values of time and cost of an activity in project scheduling process because many uncertain factors, such was weather, productivity level, human factors etc., dynamically, affect them during project implementation process. A GAs-based fully fuzzy optimal time-cost trade-off model is presented based on fuzzy sets and genetic algorithms (GAs). In tihs model all parameters and variables are characteristics by fuzzy numbers. And then GAs is adopted to search for the optimal solution to this model. The method solves the time-cost trade-off problems under an uncertain environment and is proved practicable through a giving example in ship building scheduling.