MCWOA Scheduler:Modified Chimp-Whale Optimization Algorithm for Task Scheduling in Cloud Computing

Cloud computing provides a diverse and adaptable resource pool over the internet,allowing users to tap into various resources as needed.It has been seen as a robust solution to relevant challenges.A significant delay can hamper the performance of IoT-enabled cloud platforms.However,efficient task scheduling can lower the cloud infrastructure’s energy consumption,thus maximizing the service provider’s revenue by decreasing user job processing times.The proposed Modified Chimp-Whale Optimization Algorithm called Modified Chimp-Whale Optimization Algorithm(MCWOA),combines elements of the Chimp Optimization Algorithm(COA)and the Whale Optimization Algorithm(WOA).To enhance MCWOA’s identification precision,the Sobol sequence is used in the population initialization phase,ensuring an even distribution of the population across the solution space.Moreover,the traditional MCWOA’s local search capabilities are augmented by incorporating the whale optimization algorithm’s bubble-net hunting and random search mechanisms into MCWOA’s position-updating process.This study demonstrates the effectiveness of the proposed approach using a two-story rigid frame and a simply supported beam model.Simulated outcomes reveal that the new method outperforms the original MCWOA,especially in multi-damage detection scenarios.MCWOA excels in avoiding false positives and enhancing computational speed,making it an optimal choice for structural damage detection.The efficiency of the proposed MCWOA is assessed against metrics such as energy usage,computational expense,task duration,and delay.The simulated data indicates that the new MCWOA outpaces other methods across all metrics.The study also references the Whale Optimization Algorithm(WOA),Chimp Algorithm(CA),Ant Lion Optimizer(ALO),Genetic Algorithm(GA)and Grey Wolf Optimizer(GWO).

Impacts of the Financial Factors on Schedule Delays Risk of the International Contracting Projects: Evidence from Highway BOT Pro-jects in Vietnam

Vietnam has become a major market for construction enterprises from East Asian countries, especially from China, to participate in international project contracting, but serious schedule delays have important adverse effects on local government and foreign investment companies. Based on international engineering contracting mode of Vietnam highway BOT construction projects, we discussed the drive financial factors of schedule delays, using the methods of exploratory factor analysis and questionnaire survey, and evaluated the effects of various factors which are through regression analysis. The empirical results show that the five categories of financial factors, including the policy change, slow payment, financial mismanagement, financial market changes and lack of fiscal, have significant effects on schedule delay. Furtherly, we suggested that strengthening policy research and improving financial management ability should be used to reduce the influence of relevant financial factors on schedule delay, to improve the profitability of international businesses and the motivation of foreign enterprises to participate in Vietnam highway project.

Optimization of project payment schedules with Nash equilibrium model and genetic algorithm

To minimize the deviations of the net present values of project payment for both the owner and the client and optimize project payment schedules, a Nash equilibrium model based on game theory was set up and a genetic algorithm was developed to work out the Nash equilibrium solution with a two-stage backward inductive approach that requires the client responds to the owner’s payment schedule with an activity schedule so as to maximize the client’s net present value of cash flows. A case study demonstrated that a payment schedule at the Nash equilibrium position enables both the owner and the client to gain their desirable interests, thus is a win-win solution for both parties. Despite the computation time of the proposed algrithm in need of improving, combining Nash equilibrium and genetic algorithm into a complete-information dynamic-game model is a promising method for project management optimization.

Yield and Nutritive Values of Semi- and Non-Fall Dormant Alfalfa Cultivars under Late-Cutting Schedule in California’s Central Valley

California is one of the major alfalfa (Medicago sativa L) forage-producing states in the U.S, but its production area has decreased significantly in the last couple of decades. Selection of cultivars with high yield and nutritive value under late-cutting schedule strategy may help identify cultivars that growers can use to maximize yield while maintaining area for sustainable alfalfa production, but there is little information on this strategy. A field study was conducted to determine cumulative dry matter (DM) and nutritive values of 20 semi- and non-fall dormant (FD) ratings (FD 7 and FD 8 - 10, respectively) cultivars under 35-day cut in California’s Central Valley in 2020-2022. Seasonal cumulative DM yields ranged from 6.8 in 2020 to 37.0 Mg·ha−1 in 2021. Four FD 8 - 9 cultivars were the highest yielding with 3-yrs avg. DM greater than the lowest yielding lines by 46%. FD 7 cultivar “715RR” produced the highest crude protein (CP: 240 g·Kg−1) while FD 8 cultivar “HVX840RR” resulted in the highest neutral detergent fiber digestibility (NDFD: 484 g·Kg−1, 7% greater than the top yielding cultivars) but with DM yield intermediate. Yields and NDFD correlated positively but weakly indicating some semi- and non-FD cultivars performing similarly. These results suggest that selecting high yielding cultivars under 35-day cutting schedule strategy can be used as a tool to help growers to maximize yield while achieving good quality forages for sustainable alfalfa production in California’s Central Valley.

Real-time and dynamic schedule optimization of construction projects on the basis of lean construction

Lean construction has been newly applied to construction industry. The best performance of a project can be achieved through the precise definition of construction product, rational work break structure, lean supply chain, decrease of resources waste, objective control and so forth. Referring to the characteristics of schedule planning of construction projects and lean construction philosophy, we proposed optimizing methodology of real-time and dynamic schedule of construction projects based on lean construction. The basis of the methodology is process reorganization and lean supply in construction enterprises. The traditional estimating method of the activity duration is fuzzy and random;however, a newly proposed lean forecasting method employs multi-components linear-regression, back-propagation artificial neural networks and learning curve. Taking account of the limited resources and the fixed duration of a project, the optimizing method of the real-time and dynamic schedule adopts the concept of resource driving. To optimize the schedule of a construction project timely and effectively, an intellectualized schedule management system was developed. It can work out the initial schedule, optimize the real-time and dynamic schedule, and display the schedule with the Gant Chart, the net-work graph and the space-time line chart. A case study was also presented to explain the proposed method.

Analyses on schedule-cost coefficient correlation of spaceflight project based on historical statistics and its application

When analyze the uncertainty of the cost and the schedule of the spaceflight project, it is needed to know the value of the schedule-cost correlation coefficient. This paper deduces the schedule distribution, considering the effect of the cost, and proposes the estimation formula of the correlation coefficient between the in（schedule） and the cost. On the basis of the fact and Taylor expansion, the relation expression between the schedule-cost correlation coefficient and the in-schedule-cost correlation coefficient is put forward. By analyzing the value features of the estimation formula of the in-schedule-cost correlation coefficient, the general rules are proposed to ascertain the value of the schedule-cost correlation coefficient. An example is given to demonstrate how to approximately amend the schedule-cost correlation coefficient based on the historical statistics, which reveals the traditional assigned value is inaccurate. The universality of this estimation method is analyzed.

Schedule Control of Coal Mine Construction Projects Based on Factor Analysis

Schedule management is the crucial capability for large-scale coal mining investors to successful finish the construction project, which could get by the accumulation of the long-time institutional executive force and ability training. By using factor analysis and validation analysis, extracted control factors of schedule management from data have been made in large coal mine construction companies. Some control factors have a greater influence on the schedule management which are the system factor, measures factor, economic controlling factor, behavioral factor, process factor, organization factor, thus the enterprise schedule management system should include the terms of the above factors.

Estimation Method of Schedule-cost Correlation Coefficient of Spaceflight Project

To evaluate the cost risk and the schedule risk of the spaceflight project,the schedule-cost(S-C) correlation coefficient is directly appointed according to the experts' experience usually.This paper deduces SDMCU(the schedule distribution model considering the effect of the cost uncertainty),and then proposes the approximate formula to estimate the ln(S)-C correlation coefficient based on the models of SDMCU and CDMSU(the cost distribution model considering the effect of the schedule uncertainty).Furthermore,an approximate relationship expression of the S-C and the ln(S)-C correlation coefficients is put forward according to general facts and the Taylor expansion,and advanced by means of mass numerical validation is the general rule of obtaining the estimation value of the schedule-cost correlation coefficient based on the historical data.

Schedule Model for Project Portfolio Based on Design Structure Matrix

To improve the enterprise resource utilization and shorten the cycle of the whole project portfolio, a scheduling model based on Design Structure Matrix （DSM） is built. By setting the project activity weight index system and calculating the activity weight for the project portfolio, the constraint relationship between project portfolio information and resource utilization, as the two dimensions of the DSM, are fully reflected in the sched- ule model to determine the order of these activities of project portfolio. A project portfolio example is given to il- lustrate the applicability and effectiveness of the schedule model.

Stochastic Earned Duration Analysis for Project Schedule Management

Earned duration management(EDM)is a methodology for project schedule management(PSM)that can be considered an alternative to earned value management(EVM).EDM provides an estimation of devia-tions in schedule and a final project duration estimation.There is a key difference between EDM and EVM:In EDM,the value of activities is expressed as work periods;whereas in EVM,value is expressed in terms of cost.In this paper,we present how EDM can be applied to monitor and control stochastic pro-jects.To explain the methodology,we use a real case study with a project that presents a high level of uncertainty and activities with random durations.We analyze the usability of this approach according to the activities network topology and compare the EVM and earned schedule methodology(ESM)for PSM.

Application of Earned Value Method in Project Cost Management and Schedule Management

At present,with the rapid development of China's economy,the development of the construction industry has made a new breakthrough.Project management requires the construction industry to continuously play its role and value in improving the ability of project management.Earned value method,which is an important way in the field of project management,enables whole project management to rise to a new height.The specific principle of earned value method will be elaborated by fully introducing the specific role of earned value method in engineering projects to provide a reference and basis for practitioners to improve their management ability.

Multi-objective integrated optimization based on evolutionary strategy with a dynamic weighting schedule

The evolutionary strategy with a dynamic weighting schedule is proposed to find all the compromised solutions of the multi-objective integrated structure and control optimization problem, where the optimal system performance and control cost are defined by H2 or H∞ norms. During this optimization process, the weights are varying with the increasing generation instead of fixed values. The proposed strategy together with the linear matrix inequality （LMI） or the Riccati controller design method can find a series of uniformly distributed nondominated solutions in a single run. Therefore, this method can greatly reduce the computation intensity of the integrated optimization problem compared with the weight-based single objective genetic algorithm. Active automotive suspension is adopted as an example to illustrate the effectiveness of the proposed method.

STK/Scheduler在卫星数传调度中的应用研究

卫星数传调度问题是一类复杂的组合优化问题,即如何为卫星数传任务分配地面资源的问题,它是当前航天领域需要重点研究的问题之一。STK/Scheduler模块是STK工具包中的调度模块,对外提供了二次开发功能。针对卫星数传调度问题,研究了STK/Scheduler模块在该问题中的应用。首先在分析问题的基础上建立了卫星数传任务模型和调度模型,然后对基于STK/Scheduler的卫星数传调度系统进行了设计。最后利用AFIT基准数据进行了验证,结果表明在卫星数传任务规模不太大的情况下,STK/Scheduler为卫星数传调度问题的求解提供了一条捷径。

基于Linux的集群系统中联合调度(Co-Scheduler)模块的设计

在集群系统中,调度模块的设计对整个系统的性能而言是至关重要的。文章针对以Linux操作系统为平台的集群系统,提出了一种联合调度模块的实现方案。该方案在不改动Linux内核的前提下,实现了基于并行作业级的调度,从而大大提高了集群系统的性能和资源的协调利用率。

具有时变柔性负载的电液力控制系统中Gain-Scheduled H_∞控制器的研究

针对具有时变柔性负载的电液力控制系统设计了 Ｇａｉｎ－ Ｓｈｅｄｕｌｅｄ Ｈ_∞控制器。 Ｇａｉｎ－ Ｓｈｃｈｅｄｕｌｅｄ Ｈ_∞控制适用于状态空间矩阵是时变参数的线性函数的慢时变系统。其控制器的形式可根据时变参数的变化实时地进行调节，以满足不同时刻系统的性能要求。将该方法应用到了液压式全自动地震波输入振动三轴装置中（以下简称动三轴）。仿真结果表明Ｇａｉｎ一Ｓｃｈｅｄｕｌｅｄ Ｈ_∞控制方法对改善负载参数变化较大的动三轴的性能是非常有效的。

基于STK/Scheduler的航天任务调度应用研究

STK/Scheduler是与STK（satellite tool kits）完全集成的任务调度软件,通过它可方便的定义任务、资源和各种约束关系。介绍了STK/Scheduler的主要功能,在分析航天任务调度的特点及要素的基础上,建立了调度模型,并利用STK/Scheduler实现了2个典型的卫星任务调度。结果表明：STK/Scheduler能基本满足航天任务调度的需求。

基于神经网络的GAIN-SCHEDULED飞行控制器设计方法研究

采用神经网络设计ＧＡＩＮＳＣＨＥＤ－ＵＬＥＤ控制器，给出神经网络ＧＡＩＮ－ＳＣＨＥＤＵＬ－ＩＮＧ控制器的实现方法，这样做可以简化控制器的ＳＣＨＥＤＵＬＩＮＧ参数，并且能够区分不同条件下的控制器结构。将其用于飞行控制器的设计，验证了所提方法的有效性。

Hybrid ant colony optimization for the resource-constrained project scheduling problem

To solve the resource-constrained project scheduling problem （RCPSP）, a hybrid ant colony optimization （HACO） approach is presented. To improve the quality of the schedules, the HACO is incorporated with an extended double justification in which the activity splitting is applied to predict whether the schedule could be improved. The HACO is tested on the set of large benchmark problems from the project scheduling problem library （PSPLIB）. The computational result shows that the proposed algo- rithm can improve the quality of the schedules efficiently.