Design of tall bridge piers by ant colony optimization

This paper describes a methodology for the analysis and design of Reinforced Concrete (RC) tall bridge piers with hollow rectangular sections, which are typically used in deep valley bridge viaducts. Piers are usually considered tall when the shaft has a height of 50 m or more. Three different types of rectangular hollow tall piers have been studied for road piers of 90.00 m in height: RTRA90, RLON90 and RLT90. RTRA90 has the two side walls inclined, RLON90 has the two frontal walls inclined and RLT90 has all four walls inclined. The procedure used in the present study to solve the combinatorial problem is a variant of the ant colony optimization. RTRA90 leads to the most economical pier, both in column and foundation cost, since it is the most efficient set up for horizontal loads. Regarding the cost of the vertical column only, i.e. excluding the foundation, the cost of RTRA90 and RLON90 are similar, but the cost of the column RLT90 is higher due to its larger unit cost of interior formwork.     

A particle swarm ant colony optimization for truss structures with discrete variables

In this paper, a particle swarm optimizer with passive congregation (PSOPC), ant colony optimization (ACO) and harmony search scheme (HS) are combined to reach to an efficient algorithm, called discrete heuristic particle swarm ant colony optimization (DHPSACO). This method is then employed to optimize truss structures with discrete variables. The DHPSACO applies a PSOPC for global optimization and the ant colony approach for local search, similar to its continuous version. The problem-specific constraints are handled using a modified feasible-based mechanism, and the harmony search scheme is employed to deal with variable constraints. Some design examples are tested using the new method and their results are compared to those of PSO, PSOPC and HPSO algorithms to demonstrate the effectiveness of the present method.     

Performance-based seismic design of steel frames using ant colony optimization

In this paper, a performance-based optimal seismic design of frame structures is presented using the ant colony optimization (ACO) method. This discrete metaheuristic algorithm leads to a significant improvement in consistency and computational efficiency compared to other evolutionary methods. A nonlinear analysis is utilized to arrive at the structural response at various seismic performance levels, employing a simple computer-based method for push-over analysis which accounts for first-order elastic and second-order geometric stiffness properties. Two examples are presented to illustrate the capabilities of ACO in designing lightweight frames, satisfying multiple performance levels of seismic design constraints for steel moment frame buildings, and a comparison is made with a standard genetic algorithm (GA) implementation to show the superiority of ACO for the discussed optimization problem.     

Optimal transient network rehabilitation using multi-objective ant colony optimization algorithm

ABSTRACT

In this paper, the problem of optimal rehabilitation of water distribution networks (WDNs) for both steady and transient state is investigated. Two objectives are considered in this study: minimizing rehabilitation cost by considering pipe size diameters as decision variables and minimizing the transient impacts by minimizing a surge damage potential factor (SDPF). A multi-objective ant colony optimization (MOACO) model is developed to solve this problem. The developed model is verified using the well-known New York City tunnel network. The application is carried out to modify an existing real WDN in New Cairo district designed in steady-state conditions to cope with the transient condition. The advantage of this study is to produce a set of solutions that help decision makers to identify the suitable approach, while evaluating and aggregating the preferences over multiple objective functions.     

蚁群算法在雨水管道系统优化设计中的新尝试

引入一种新的优化设计方法——蚁群算法,并探讨将该法应用于雨水管道系统的优化设计.通过实例说明蚁群算法的过程,并与遗传算法进行比较,表明蚁群算法在给排水管网设计中有较为广阔的应用前景.     

Simulation optimization for earthmoving operations using genetic algorithms

This paper presents a methodology for simulation optimization utilizing genetic algorithms and applies it to a newly developed simulation-based system for estimating the time and cost of earthmoving operations. The genetic algorithm searches for a near-optimum fleet configuration that reduces project total cost, and considers a set of qualitative and quantitative variables that influence earthmoving operations. Qualitative variables represent the models of equipment used in each fleet scenario, whereas quantitative variables represent the number of items of equipment involved in each scenario. Pilot simulation runs were carried out for all configurations generated by the developed algorithm, and a complete simulation analysis was then performed for the fleet recommended by the algorithm. The numerical example demonstrates the use of the proposed methodology and illustrates its essential features.     

粒子群-鱼群混合算法在桁架结构优化设计中的应用

群智能算法由于其优异的搜索性能被广泛应用于结构优化设计,人工鱼群算法和粒子群算法都是基于动物群体行为的智能优化随机算法.本文介绍了人工鱼群算法和粒子群算法的基本原理,并提出了粒子群和鱼群杂交混合的一种新方法:粒子群-鱼群混合算法,将粒子群-鱼群混合算法应用到四个桁架结构的重量优化设计,包括平面桁架结构和空间桁架结构,通过比较粒子群-鱼群混合算法、人工鱼群算法、粒子群算法的优化结果,发现改进的粒子群-鱼群混合算法具有收敛精度高、收敛速度快等特点,同时具有较好的稳定性,可用于结构优化设计.     

An optimization method for selecting project risk response strategies

There is wide agreement that the risk response strategy selection is an important issue in project risk management (PRM). Some academic researchers have paid attention to this issue. This paper proposes a novel method for solving the risk response strategy selection problem in PRM. In the method, an optimization model is developed, which integrates three critical elements that are the project cost, project schedule and project quality. By solving the model, the optimal solution could be obtained so that the most desirable risk response strategies to cope with the risk events can be determined. If the optimal solution is not found or project managers are not satisfied with the solution, another pathway can be used to support the managers to get the desirable strategies. The pathway is based on an iterative process which involves making trade-offs between the project budget, time and quality according to objective requirements and managers' judgments. The iterative process comes to an end if the objectives predefined by the managers are reached. A simple example project is also provided to illustrate the practicality and usefulness of the proposed method.     

A performance comparison of multi-objective optimization algorithms for solving nearly-zero-energy-building design problems

Integrated building design is inherently a multi-objective optimization problem where two or more conflicting objectives must be minimized and/or maximized concurrently.Many multi-objective optimization algorithms have been developed;however few of them are tested in solving building design problems.This paper compares performance of seven commonly-used multi-objective evolutionary optimization algorithms in solving the design problem of a nearly zero energy building(n ZEB) where more than 1.610 solutions would be possible.The compared algorithms include a controlled non-dominated sorting genetic algorithm witha passive archive(p NSGA-II),a multi-objective particle swarm optimization(MOPSO),a two-phase optimization using the genetic algorithm(PR_GA),an elitist non-dominated sorting evolution strategy(ENSES),a multi-objective evolutionary algorithm based on the concept of epsilon dominance(ev MOGA),a multi-objective differential evolution algorithm(sp MODE-II),and a multi-objective dragonfly algorithm(MODA).Several criteria was used to compare performance of these algorithms.In most cases,the quality of the obtained solutions was improved when the number of generations was increased.The optimization results of running each algorithm20 times with gradually increasing number of evaluations indicated that the PR_GA algorithm had a high repeatability to explore a large area of the solution-space and achieved close-to-optimal solutions with a good diversity,followed by the p NSGA-II,ev MOGA and sp MODE-II.Uncompetitive results were achieved by the ENSES,MOPSO and MODA in most running cases.The study also found that 1400-1800 were minimum required number of evaluations to stabilize optimization results of the building energy model.     

A unified approach to parameter selection in meta-heuristic algorithms for layout optimization

Meta-heuristic optimization algorithms have attracted many researchers in the last decade. Adjustment of different parameters of these algorithms is usually a time consuming task which is mostly done by a trial and error approach. In this study an index, namely convergence factor (CF), is introduced that can show the performance of these algorithms. CF of an algorithm provides an estimate of the suitability of the parameters being set and can also enforce the algorithm to adjust its parameters automatically according to a pre-defined CF.In this study GA, ACO, PSO and BB-BC algorithms are used for layout (topology plus sizing) optimization of steel braced frames. Numerical examples show these algorithms have some similarities in common that should be taken into account in solving optimization problems.     

Improved methods for determining the 3 dimensional initial shapes of cable-supported bridges

The TCUD method (Kim and Lee, 2001) can minimize undesirable lateral displacements in cable bridge structures by including the unstrained lengths of the cable members as unknowns and introducing additional constraint conditions. The axial deformations in the girder and the main tower deviating from the target configuration are, however, unavoidable when self-anchored cable bridges are considered. On the other hand, the IFM (initial force method) can be used to adjust the axial deformations to conform to the initial shape but it is critical that the unstrained lengths of the cables are accurately evaluated. In this study, improved schemes for the TCUD method and the IFM for finding the initial shape of 3 dimensional cable-supported bridges under dead load, are presented. For this purpose, the TCUD method and the initial force method are firstly reviewed. Two improved algorithms, which can overcome shortcomings of the previous initial-shaping analysis methods, are developed based on an elastic catenary cable element and a nonlinear space frame element. Finally, the accuracy and effectiveness of the proposed analysis algorithms are demonstrated through the numerical application to 3 dimensional initial shape problems for self-anchored suspension and cable-stayed bridges.     

改进的高性能混凝土配合比优化设计的三功能准则

提出了改进的高性能混凝土配合比优化设计三功能准则,根据具体的工程要求采用层次分析法设置权重以减少人为因素的影响。用总功效系数最大作为优化准则。实际工程应用表明．改进的准则优化结果可靠且可操作性强,具有较高的工程应用价值。     

关键链技术在军用电子元器件领域的应用研究

军用电子元器件项目具有种类繁多、研制周期短、用户要求分散等特点,传统里程碑式的管理方法已无法满足当前多项目研制需求。关键链技术作为项目管理的研究热点,其核心理念是寻找项目制约因素,突破瓶颈资源,提升效率。在现有质量体系要求下,运用关键链技术分析方法,找到多项目研制过程中的瓶颈资源,根据项目特点设置合理可行的缓冲区,调整资源,突破瓶颈资源的约束,并进行监督跟踪,确保多项目研制的顺利进行,提高项目研发效率和按时完成率。     

用项目驱动法优化建筑学实践教学的探索

针对建筑学专业课外实践与课内的设计训练缺乏应有的联系,达不到预期的效果的情况,尝试通过一系列的驱动项目,把各类实践教学串联成一个完整的课程体系,用项目来驱动课外实践教学,同时实践教学也使课内的设计训练更加务实有效,从而提高学生的实践能力及专业素养。     

Fuzzy critical chain method for project scheduling under resource constraints and uncertainty

This paper develops a fuzzy critical chain method for project scheduling under resource constraints and uncertainty. The method consists of developing a desirable deterministic schedule under resource constraints, and adding a project buffer (PB) to the end of the schedule to deal with uncertainty. The size of the project buffer is determined by computations with fuzzy numbers. During project execution, the proposed method focuses on the penetration level in the project buffer, and dynamically updates the schedule to provide a more accurate schedule for actual progress. The use of a project buffer makes the method akin to critical chain project management (CCPM), although no feeding buffers are used. The proposed method is useful for both project planning and execution.     

Improved strategies and optimization of calibration models for real-time PCR absolute quantification

Real-time PCR absolute quantification applications are becoming more common in the recreational and drinking water quality industries. Many methods rely on the use of standard curves to make estimates of DNA target concentrations in unknown samples. Traditional absolute quantification approaches dictate that a standard curve must accompany each experimental run. However, the generation of a standard curve for each qPCR experiment set-up can be expensive and time consuming, especially for studies with large numbers of unknown samples. As a result, many researchers have adopted a master calibration strategy where a single curve is derived from DNA standard measurements generated from multiple instrument runs. However, a master curve can inflate uncertainty associated with intercept and slope parameters and decrease the accuracy of unknown sample DNA target concentration estimates. Here we report two alternative strategies termed ‘pooled’ and ‘mixed’ for the generation of calibration equations from absolute standard curves which can help reduce the cost and time of laboratory testing, as well as the uncertainty in calibration model parameter estimates. In this study, four different strategies for generating calibration models were compared based on a series of repeated experiments for two different qPCR assays using a Monte Carlo Markov Chain method. The hierarchical Bayesian approach allowed for the comparison of uncertainty in intercept and slope model parameters and the optimization of experiment design. Data suggests that the ‘pooled’ model can reduce uncertainty in both slope and intercept parameter estimates compared to the traditional single curve approach. In addition, the ‘mixed’ model achieved uncertainty estimates similar to the ‘single’ model while increasing the number of available reaction wells per instrument run.     

岩溶地区工程建设项目方案的勘察优选分析

以某规划区建筑工程项目为例，在工程地质勘察的基础上，根据所收集到的地质资料，对岩溶地区重大工程建设项目工程地质条件作了详细分析论证，对比论证了建设项目方案的优劣，为有关部门方案优选提供了重要依据。     

蒸馏分离-汞盐滴定法测定混凝土样品中氯含量方法的改进

混凝土中的氯含量过高会严重锈蚀钢筋,因此混凝土中氯的检测显得尤为重要,由于混凝土样品中既含有水泥、砂石等无机材料,又可能含有各种有机材料外加剂,因此很难找到直接测试混凝土中氯的方法.本文对蒸馏法的装置进行了改进用来测定混凝土中的氯含量,通过实验证实了方法的可靠性.     

浅析LINGO软件在工期资源优化中的应用

论述了施工组织中常遇到的“资源有限一工期最短”的优化问题,分析了传统网络计划优化存在的问题,并举一工程实例,给出了LINGO软件包的基本原理和优势,并对工程实例进行优化求解,使得“资源有限一工期最短”的优化问题变得快速而便捷完成。