Search

Time–cost trade-off analysis is addressed as an important aspect of any construction project planning and control. Nonexistence of a unique solution makes the time–cost trade-off problems very difficult to tackle. As a combinatorial optimization problem one may apply heuristics or mathematical programming techniques to solve time–cost trade-off problems. In this paper, a new multicolony ant algorithm is developed and used to solve the time–cost multiobjective optimization problem. Pareto archiving together with innovative solution exchange strategy are introduced which are highly efficient in developing the Pareto front and set of nondominated solutions in a time–cost optimization problem. An 18-activity time–cost problem is used to evaluate the performance of the proposed algorithm. Results show that the proposed algorithm outperforms the well-known weighted method to develop the nondominated solutions in a combinatorial optimization problem. The paper is more relevant to researchers who are interested in developing new quantitative methods and/or algorithms for managing construction projects. [ABSTRACT FROM AUTHOR]

Dynamic site layout planning requires identifying and updating the positions of all temporary construction facilities such as offices, storage areas, and workshops over the entire project duration. Existing models do not guarantee global optimal solutions because they focus on optimizing the planning and layout of successive construction stages in a chronological order, without considering the future implications of layout decisions made in early stages. This paper presents the development of an approximate dynamic programming model that is capable of searching for and identifying global optimal dynamic site layout plans. The model applies the concepts of approximate dynamic programming to estimate the future effects of layout decisions in early stages on future decisions in later stages. The model is developed in three main phases: (1) formulating the decision variables, geometric constraints, and objective function of the dynamic site layout planning problem; (2) modeling the problem using approximate dynamic programming; and (3) implementing and evaluating the performance of the model. An evaluation example is analyzed to illustrate the use of the model and demonstrate its capabilities in generating global optimal solution for dynamic site layout planning of construction projects. [ABSTRACT FROM AUTHOR]

Semidefinite programming (SDP) provides a convenient framework for the solution of optimization problems involving the eigenvalues of symmetric matrices. The classical Mohr–Coulomb yield criterion for an isotropic cohesive-frictional continuum is most naturally expressed in terms of principal stresses (eigenvalues of the symmetric stress tensor), while the associated flow rule and plastic dissipation function can both be expressed in terms of principal strains (eigenvalues of the symmetric strain tensor). This suggests that SDP could be suitable for performing limit analysis of three-dimensional (3D) structures obeying the Mohr–Coulomb criterion, where the yield and flow rule constraints are difficult to enforce using other methods of optimization. In this paper it is demonstrated that SDP can indeed be used to obtain both lower and upper bounds on the exact collapse load for a Mohr–Coulomb continuum in 3D, though a novel derivation is needed to arrive at an efficient SDP formulation of the upper bound in terms of kinematic quantities only. Two numerical examples are studied, using finite-element discretizations of the stress and displacement fields that preserve the strictness of the lower and upper bound solutions. The arising optimization problems are solved using the general-purpose SDP solver SeDuMi, with no attempt to modify or tailor the code for this specific application. Even so, 3D analyses of moderate size (several thousand tetrahedral elements) are handled with encouraging efficiency. [ABSTRACT FROM AUTHOR]

The construction industry in the United States and other parts of the world has been facing several challenges, including a shortage of skilled workers. A review of the relevant body of knowledge indicates that one of the key reasons for this problem is the absence of human resource management strategies for construction workers at project, corporate, regional, or industry levels. This paper addresses the issues of workforce training and allocation on construction projects. It presents a framework to optimize the investment in, and to make the best use of, the available workforce with the intent to reduce project costs and improve schedule performance. A linear program model, entitled the Optimal Workforce Investment Model, is built to provide an optimization-based framework for matching supply and demand of construction labor most efficiently through training, recruitment, and allocation. Given a project schedule or demand profile and the available pool of workers, the suggested model provides human resource managers a combined strategy for training the available workers and hiring additional workers. The input data to the proposed model consists of a certain available labor pool, cost figures for training workers in different skills, the cost of hiring workers, hourly labor wages, and estimates of affinities between the different considered skills. The objective of the model is to minimize labor costs while satisfying project labor demands. Results from application of the model to typical situations are presented, and recommendations for future developments are made. [ABSTRACT FROM AUTHOR]

Practical optimization of infrastructure preservation works programming has always posed a computational challenge due to the complexity and scale of the problem. Critical to the process is formulations in which the identity of individual projects is preserved. This requirement leads to exponential growth of solution space, often resulting in an unmanageable process using traditional analytical optimization techniques. In this paper, we propose an evolutionary-based multiyear optimization procedure for solving network level infrastructure works programming problems using a relatively new concept known as the shuffled complex evolution algorithm. A case study problem is analyzed to illustrate the robustness of the technique. The findings show convergence characteristics of the solution and demonstrate that the algorithm is very efficient and consistent in simultaneous consideration of the trade-off among various infrastructure preservation strategies. It is concluded that the robust search capability of the shuffled complex evolution technique is well suited for solving the combinatorial problems in network level infrastructure preservation works programming. [ABSTRACT FROM AUTHOR]

This study introduces the weed optimization algorithm (WOA) to optimal reservoir operation. The WOA is a metaheuristic optimization method inspired by weeds' life cycle. The effectiveness of the WOA is demonstrated with the optimization of mathematical functions and reservoir systems. The WOA is applied in continuous-time and discrete-time formulations of reservoir-operation optimization and its results are compared with global optimal solutions obtained with nonlinear programming (NLP), linear programming (LP), and the genetic algorithm (GA). The results show the WOA's fast convergence to solutions that are very near the global optimal solutions of the reservoir optimization problems. [ABSTRACT FROM AUTHOR]

By incorporating the variation of soil friction angle ([lowercase_phi_synonym]) with mean principal stress (σm), the effect of footing width (B) on bearing capacity factor Nγ was examined for a smooth strip footing placed on a granular medium without any surcharge pressure. The analysis was performed by means of a numerical lower bound limit analysis in conjunction with finite-elements and linear programming. An iterative computational procedure was framed to account for the dependency of [lowercase_phi_synonym] on σm. Two well-defined [lowercase_phi_synonym]–σm curves from literature associated with Hoston and Toyora sands, corresponding to relative density of 18 and 74.5%, respectively, were used. The magnitude of Nγ was obtained for different footing widths, covering almost the entire range of model and field footing sizes. It was noted that for B greater than about 0.4 m, it is possible to relate Nγ with B approximately in a linear fashion on a log–log scale. Further, it was seen that if an average value of [lowercase_phi_synonym] along the footing–soil interface is obtained, it is possible to estimate a reasonable magnitude of Nγ for a given footing width provided the relationship between [lowercase_phi_synonym] and σm is specified for the given material. [ABSTRACT FROM AUTHOR]