Application of RFID tracking to the optimization of function-space assignment in buildings

Function–space assignment, which allocates a function for each space in a facility, is one of the most important factors in determining the usability performance of a building. Most architects renovate a building based on their personal perception of how the occupants might use the building instead of quantitatively analyzing their use behaviors. This study developed a function–space assignment optimization model based on the occupants' movement data as tracked by RFID technology. The model mines the movement data by constructing patterns and calculating the relation values between functions. The search for the best assignment is based on the fast messy genetic algorithm (fmGA) with the objective function incorporating the preference of space size and the minimization of the distance for movement required by the occupants during the performance of their daily activities. The proposed model incorporated building-block filtering mechanism in the fmGA problem-solving process to generate enough copies of the good building blocks so more copies would remain for subsequent processing. The paper also describes two experiments that evaluate the performance of the model and compare the performances of the models with and without the building-block filtering mechanism.     

The Multimode Resource‐Constrained Project Scheduling Problem for Repetitive Activities in Construction Projects

In construction projects, resource availability might limit the implementation of ideal schedules. Especially, when repetitive activities are involved, traditional resource‐constrained project scheduling problem (RCPSP) models fail to allocate the resource consumption in an efficient manner. Besides, actual models only provide local optimal solutions and do not incorporate activity acceleration routines. To fulfill this gap, partially, a mathematical optimization model, the multimode RCPSP for repetitive activities in construction projects, is proposed and solved to optimality; it takes into account acceleration routines under real construction scenarios using spreadsheets. The article shows a complete computational experimentation over a real construction project, considering several scenarios of resource availabilities and continuity conditions. The model allows analyzing the resources efficiency indexes comparing them to resource consumptions, continuity of activities, and objective functions that reveal that fragmented activities do not provide better resource efficiency outcomes.     

三联供与冰蓄冷耦合的复合系统优化设计

本文建立了一个冷热电三联供与冰蓄冷耦合的复合系统优化数学模型,以年总运行成本最小为目标函数,综合考虑了经济性、环保性、节能性评价指标对系统的影响。最后以上海某综合型超高层建筑为研究对象,利用LINGO软件进行多目标优化计算,提出了三联供耦合冰蓄冷系统的设备优化容量以及全年运行策略优化方案,并分析了电、气价格及二氧化碳排放税对系统的影响。     

Surrogate‐based toll optimization in a large‐scale heterogeneously congested network

Toll optimization in a large‐scale dynamic traffic network is typically characterized by an expensive‐to‐evaluate objective function. In this paper, we propose two toll‐level problems (TLPs) integrated with a large‐scale simulation‐based dynamic traffic assignment model of Melbourne, Australia. The first TLP aims to control the pricing zone (PZ) through a time‐varying joint distance and delay toll such that the network fundamental diagram (NFD) of the PZ does not enter the congested regime. The second TLP is built upon the first TLP by further considering the minimization of the heterogeneity of congestion distribution in the PZ. To solve the two TLPs, a computationally efficient surrogate‐based optimization method, that is, regressing kriging with expected improvement sampling, is applied to approximate the simulation input–output mapping, which can balance well between local exploitation and global exploration. Results show that the two optimal TLP solutions reduce the average travel time in the PZ (entire network) by 29.5% (1.4%) and 21.6% (2.5%), respectively. Reducing the heterogeneity of congestion distribution achieves higher network flows in the PZ and a lower average travel time or a larger total travel time saving in the entire network.     

A model for assessing occupant flow in building spaces

As buildings are becoming larger in size, the need to efficiently plan and predict the occupant movement in building spaces is gaining more attention and importance. Occupant movement in large public buildings such as train stations, airports, universities, hospitals, and shopping centers needs to be carefully analyzed and predicted for safety and also for other issues such as the level of service (LOS), comfort, and short-term planning. Currently there are many detailed occupant/pedestrian simulation models that can predict the level of service in corridors and other dynamic spaces in the building in terms of occupant flow. However, these simulation models require a well-formulated design with detailed design features. In addition, significant investment in time and effort is required in order to build the models for simulation analysis. Therefore, there is a need for a simple and quick analysis method to aid in the sizing and design of building spaces during the early design stages so that these spaces can accommodate occupant flow efficiently and safely. This paper presents a method to evaluate the LOS of occupants in dynamic buildings spaces without the need for building and running detailed simulations, so that designers can understand how well a particular space accommodates occupants' movements and activities early on in the design phase. The proposed method can be used to determine the occupant flow density in a wide array of building layouts and designs as it correlates to the level of service. A mathematical model that offers a closed-form formula for sizing space for occupant flow is developed. The model is presented in this paper and validated using real-life data. Results should be of interest to practicing architects as well as researchers.     

Coupling of whole-building energy simulation and multi-dimensional numerical optimization for minimizing the life cycle costs of office buildings

The minimization of life cycle costs for building materials and operational energy consumption of a reference commercial office building model is achieved through the optimization of envelope design parameters by the use of integrated energy simulation and multi-dimensional numerical optimization techniques. The whole-building energy simulation program EnergyPlus v6.0 is coupled with GenOpt v3.0 generic optimization tool to automatically compute the optimal values of thermal insulation thicknesses for external walls and roofs in addition to glazing unit types for vertical fenestration. A life cycle cost (LCC) model is implemented within the GenOpt program for the objective function evaluation using simulation outputs pertaining to energy consumption and associated utility costs. A stochastic population-based and multi-dimensional optimization technique of Particle Swarm Optimization (PSO) is utilized for searching the parameter space. This algorithm can result in a 36.2% reduction in the computational effort to converge to the global minimum point with a very high degree of accuracy compared to the full enumeration technique. The results indicate that the annual total site energy consumption of the optimized building model is reduced by 33.3% with respect to the initial baseline case. The optimized envelope parameters can yield 28.7% life cycle cost reduction over a 25 years life span with a simple pay-back period of 4.2 years.     

Pareto-Optimal Conceptual Design of the Structural Layout of Buildings Using a Multicriteria Genetic Algorithm

This article presents a computational procedure for multicriteria optimal conceptual design of the structural layout of buildings subject to given specifications and requirements. Two objective criteria are considered for evaluating alternative designs. The first objective concerns minimizing the building project cost through minimization of a function defining the combined costs of the building structural system and the land for the building site. The second objective concerns optimizing the flexibility of floor space usage, which is a qualitative criterion that is given a quantitative form through minimization of an exponential function that relates tributary load area to the spacing of columns. A multicriteria genetic algorithm (MGA) is applied to solve the biobjective conceptual building layout design problem using Pareto optimization theory . The MGA process is shown to be similar to that of the simple genetic algorithm, except that the fitness evaluation of candidate designs is based on a distance metric related to the Pareto-optimal set. A variable‐mutation technique is introduced to maintain genetic diversity and to accelerate the stochastic search for the global optimum. An example conceptual building layout design is presented using the MGA, and the applicability and efficiency of the developed computational conceptual design procedure are discussed.     

地下配送中心功能区布局方法研究

地下配送中心功能区布局是城市地下配送中心规划的一个重要组成部分,直接关系到地下配送中心的建设与发展,对城市地下物流系统的运营也有重大影响。为了避免由于地下配送中心功能区布局不合理而引起的地下物流服务失效,本文提出了基于AutoMod仿真平台的地下配送中心功能区系统布局规划方法。本文首先分析了地下配送中心相关物流运作特性,以功能区间的相关性和搬运成本两个指标建立了功能区布局的多目标0-1整数混合规划数学模型,对指标进行了量化,利用LINGO软件对数学模型进行求解,进而对求解布局方案进行Automod仿真检验和优化,得到最终布局方案。最后,给出了算例说明本方法的可行性。该方法可以有效地分析地下配送中心功能区布局效果,对于建设地下配送中心的决策是十分重要的。     

Handling construction pollutions using multi‐objective optimization

Quantitative assessment of emissions associated with construction projects should be carried out during the planning phase of the projects. This is important to detect and highlight any excesses of residuals during the construction phase. A newly developed framework is proposed to handle construction pollution using multi‐objective optimization. The approach, utilized by the proposed framework, is based on calculating the generated pollution for each activity involved in the project, as a result of dust, harmful gases and noise. The results of the quantitative assessment are integrated in a utility function that expresses the amount of total pollution. Then, evolutionary genetic algorithms (GAs) are used to carry multi‐objective optimization, considering three objective functions (project duration, project cost and total pollution). The proposed application considers the dynamic nature of construction activities including different types of relationships and the change of activities' criticality. An actual case study is worked out to demonstrate the practical use of the proposed framework and to investigate the sensitivity of its parameters.     

高速公路服务区建筑空间环境优化策略研究

基于对高速公路服务区使用主体的行为活动和心理、生理需求的分析,针对高速公路服务区中的建筑空间环境提出一些优化措施,如功能的设置、地域风格的体现、交往空间的层次化等,并将其应用到实际工程项目中,为创造人性化的旅途驿站提供新的设计思路。     

Antithetic Method‐Based Particle Swarm Optimization for a Queuing Network Problem with Fuzzy Data in Concrete Transportation Systems

The aim of this article is to develop an antithetic method‐based particle swarm optimization to solve a queuing network problem with fuzzy data for concrete transportation systems. The concrete transportation system at the Jinping‐I Hydropower Project is considered the prototype and is extended to a generalized queuing network problem. The decision maker needs to allocate a limited number of vehicles and unloading equipment in multiple stages to the different queuing network transportation paths to improve construction efficiency by minimizing both the total operational costs and the construction duration. A multiple objective decision‐making model is established which takes into account the constraints and the fuzzy data. To deal with the fuzzy variables in the model, a fuzzy expected value operator, which uses an optimistic–pessimistic index, is introduced to reflect the decision maker's attitude. The particular nature of this model requires the development of an antithetic method‐based particle swarm optimization algorithm. Instead of using a traditional updating method, an antithetic particle‐updating mechanism is designed to automatically control the particle‐updating in the feasible solution space. Results and a sensitivity analysis for the Jinping‐I Hydropower Project are presented to demonstrate the performance of our optimization method, which was proved to be very effective and efficient compared to the actual data from the project and other metaheuristic algorithms.     

高层办公建筑空中庭院设计初探——以南充市大学科技园主楼创新创业孵化中心主楼概念方案设计为例

高层办公建筑是一种高效节地的建筑类型,在未来的城市建设中还将日益增多。随着人们对办公空间品质要求的不断提高,空中庭院作为改善高层办公建筑空间品质的有效方式,将越来越受到人们的重视。怡人的空间环境设计是空中庭院吸引人群驻足的前提条件;合理的空间秩序布置则能够提高空中庭院的使用效率;而高超适当的生态设计策略能让空中庭院在满足人们需求的前提下实现建筑的生态可持续发展。三种设计策略这三方面在空中庭院的设计中缺一不可,需要设计师把握和融合。本文笔者结合实际项目的实践与总结,以南充市大学科技园主楼创新创业孵化中心主楼概念方案设计为例从空间环境、空间秩序和生态设计三方面阐述了项目中空中庭院的设计策略。     

A comparison of global optimization algorithms with standard benchmark functions and real-world applications using EnergyPlus

There is an increasing interest in the use of computer algorithms to identify combinations of parameters that optimize the energy performance of buildings. For such problems, the objective function can be multi-modal and needs to be approximated numerically using building energy simulation programs. As these programs contain iterative solution algorithms, they introduce discontinuities in the numerical approximation to the objective function. Metaheuristics often work well for such problems, but their convergence to a global optimum cannot be established formally. Moreover, different algorithms tend to be suited to particular classes of optimization problems.

To shed light on this issue, we compared the performance of two metaheuristics, the hybrid CMA-ES/HDE and the hybrid PSO/HJ, in minimising standard benchmark functions and real-world building energy optimization problems of varying complexity. From this, we find that the CMA-ES/HDE performs well on more complex objective functions, but that the PSO/HJ more consistently identifies the global minimum for simpler objective functions. Both identified similar values in the objective functions arising from energy simulations, but with different combinations of model parameters. This may suggest that the objective function is multi-modal. The algorithms also correctly identified some non-intuitive parameter combinations that were caused by a simplified control sequence of the building energy system that does not represent actual practice, further reinforcing their utility.     

A Simulation Model for Life Cycle Project Management

This paper puts forward a simulation model specifically designed for holistic evaluation of project functionality within a life cycle project management framework. The authors describe a methodology for development of the aforementioned tool, referred to as a dynamic simulation modeling system (DSMS). The DSMS is geared toward modeling of service and manufacturing processes with hierarchical and modular modeling methodology; however, the underlying philosophy can be adopted for modeling any generic system. The enhanced modeling features and logical division of large systems into small process components and their internal linkage are the key contributions of this work. The aim of this development is to apply the simulation technique in order to evaluate the overall project functionalities from the dynamic business perspective. A set of business objective functions (i.e., life cycle objective function [LCOF]) has been employed as a basis for decision making throughout the project's life. Object-oriented programming language with the object-oriented database technology facilitates the necessary model capability. A brief case study has been used to demonstrate and discuss the model capability.     

基于因子分析的森林康养空间评价 指标体系研究

森林康养空间是开展康养活动、建立森林康养基地的基本单元。通过4组轮回专家问卷与因子分析法,收集229份问卷,筛选并构建森林康养空间评价指标体系。结果表明:1)以康养功能为核心、森林康养空间为目标的评价指标体系包含3个一级指标、6个二级指标和22个三级指标;2)森林环境资源与森林空间特征是评价森林康养空间的决定性条件;3)森林康养空间特征主要体现在环境舒适性、设施便捷性与空间规模性3方面;4)改善空气负离子浓度、空间可达性、设施保健功能适宜性、道路联通性、设施服务半径覆盖度和森林气候舒适度等指标可以显著提升森林康养空间康养效果。本研究成果能为森林康养空间规划设计及康养效果优化提供一定的理论支撑。     

BIM技术在长江传媒大厦项目中阶段性应用(一)

本文介绍了BIM技术在武汉长江传媒大厦项目中现阶段的应用,该项目为超高层大型公建项目,其内部管线密集且对空间净空要求高,以及在大跨度钢结构拼装吊装等施工工艺以及工序方案上问题较多,通过BIM技术在利用信息模型对项目进行碰撞检查并导出管线综合排布优化图纸,对施工现场项目安全方案演示,以及对大跨度钢梁吊装等方案进行可视化演示模拟,进一步加强了BIM技术对于现场施工的指导,确保了对施工安全和质量的管理控制。     

Two‐stage profit optimization model for linear scheduling problems considering cash flow

Linear projects with repetitive activity in units are considered for investigation, and a two‐stage profit optimization model for linear scheduling problems using constraint programming (CP) is proposed. To maintain work continuity for repetitive activities, interruption time and crew availability are addressed, and the optimization process is presented as follows: (1) optimizing the primary objective (project profit); (2) minimizing total interruption time, given the optimized value of the primary objective. Repetitive activities incur batches of budget expenditure according to activity implementation time. Cash flow and financial elements are therefore integrated into the optimization model. Owing to flexible CP techniques, contractors’ requirements, such as credit limit and payment conditions, can be integrated simply into the model formulation for practical use. Lastly, a bridge example is adopted, with various constraints such as duration limitation, for scenario analysis. Consequently, the two‐stage optimization process optimizes project profit, and also maximizes work continuity for linear scheduling problems.     

Multi-objective optimization for community building group recovery scheduling and resilience evaluation under earthquake

The building group is the basis for the maintenance and operation of the city. The rapid recovery of community building group (CBG) can effectively reduce economic losses caused by earthquakes. There is service function interdependence among the buildings, and the impact of this interdependence on the postdisaster recovery of CBG is not clear. In order to improve the postdisaster recovery efficiency of CBG and explore the impact of service function dependence among buildings on postdisaster recovery, this paper integrates the recovery time (RT) and functionality loss (FL) of individual buildings and proposes two multi-objective optimization recovery models suitable for CBG: the postearthquake recovery optimization model of CBG and the postearthquake recovery optimization model of CBG considering the service function interdependence among buildings. In these models, building RT, building FL, CBG resilience, and building recovery resources are considered, and the nondominated sorting genetic algorithm-Ⅱ is used to solve the models to obtain the optimal restoration scheduling of CBG. At the same time, through a case, this paper analyzes the impact of the interdependence of service function among buildings and recovery resources on the recovery scheduling and resilience of CBG. This method can provide a basis for pre-earthquake disaster risk reduction planning and significantly improves the postdisaster recovery efficiency of CBG.     

Rectification of jacking method for brick‐wooden buildings in deformation analysis with CFST reinforcement

The tilting of buildings not only leads to inconvenience but also causes serious building collapses with heavy casualties and serious social impacts. However, rectification and reinforcement construction method started late in China. Now, this construction pattern mainly depends on sophisticated design techniques, without systematic techniques to reference. Based on the in‐depth analysis on tilt reason of a brick‐wooden building in Yunnan Province in China and combined with jacking rectification method, the impact pile project, artificial inserting shield engineering for steel box girder project, unbonded prestressed engineering project and concrete filled steel tube reinforcement example. Analyzing the multipoint synchronous lifting process by 3‐dimensional numerical simulation in ANSYS finite software. The actual monitoring results showed that the maximum inclination rate was reduced to less than 2.95‰ in the end, and the architectural distortion was stabilized in the process of rectification and reinforcement, which guarantees building safety and efficiency in the process of rectification.     

基于BIM的资源受限项目调度集成优化

建筑信息模型（BIM）发展迅速,已成为工程管理与项目管理领域研究的热点。为了实现项目调度信息集成化管理与共享,将项目调度优化与BIM技术相结合,提出了基于BIM的资源受限项目调度集成优化方法。利用BIM技术、项目调度理论以及优化算法,设计了基于BIM的资源受限项目调度集成优化框架。该框架将BIM三维模型扩展到项目调度维,采用遗传算法进行项目工期优化,利用BIM进行项目调度优化的动态模拟。通过案例验证了集成优化方法的有效性,实现了调度过程的4D动态模拟,为现场施工调度管理提供指导。