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The use of modular construction has gained wide acceptance in the industry. For a specific construction facility layout problem such as site precast standardized modular units, it requires the establishment of an on-site precast yard. Arranging the precast facilities within a construction site presents real challenge to site management. This complex task is further augmented with the involvement of several resources and different transport costs. A genetic algorithm (GA) model was developed for the search of a near- optimal layout solution. Another approach using mixed-integer programming (MIP) has been developed to generate optimal facility layout. These two approaches are applied to solve with an example in this paper to demonstrate that the solution quality of MIP outperforms that of GA. Further, another scenario with additional location constraints can also be solved readily by MIP, which, however, if modeled by GA, the solution process would be complicated. The study has highlighted that MIP can perform better than GA in site facility layout problems in which the site facilities and locations can be represented by a set of integer variables. DOI: 10.1061/(ASCE)CO.1943-7862.0000214 CE Database subject headings: Algorithms; Computer programming; Construction sites; Planning. Author keywords: Genetic algorithms; Mixed-integer programming; Facility layout.

This study proposes an integration of particle swarm optimization (PSO) and a construction simulation so as to determine efficiently the optimal resource combination for a construction operation. The particle-flying mechanism is utilized to guide the search process for the PSO-supported simulation optimization. A statistics method, i.e., multiple-comparison procedure, is adopted to compare the random output performances resulting from the stochastic simulation model so as to rank the alternatives (i.e., particle-represented resource combinations) during the search process. The indifference zone and confidence interval facilitate consideration of the secondary performance measure (e.g., productivity) when the main performance measures (e.g., cost) of the competing alternatives are close. The experimental analyses demonstrate the effectiveness and efficiency of the proposed simulation optimization. The study aims to providing an alternative combination of optimization methodology and general construction simulation by utilizing PSO and a statistics method so as to improve the efficiency of simulation in planning construction operations. CE Database subject headings: Optimization; Simulation; Construction management; Particles.

This paper introduces a particle swarm optimization (PSO)-based methodology to implement preemptive scheduling under break and resource-constraints (PSBRC) for construction projects. The PSBRC under study allows the preemptive activities to be interrupted in off-working time and not to resume immediately in the next working period because all the limited resources are to be reallocated during a break. The potential solution to the PSBRC, i.e., a set of priorities deciding the order to start the activities or restart the interrupted activities, is represented by the multidimensional particle position. Hence PSO is applied to search for the optimal schedule for the PSBRC, in which a parallel scheme is adopted to transform the particle-represented priorities to a schedule. Computational analyses are presented to verify the effectiveness of the proposed methodology. This paper provides an attempt to make use of preemption and break for the resource-constrained construction project with the objective of minimizing project duration. DOI: 10.1061/(ASCE)0733-9364(2006)132:3(259) CE Database subject headings: Optimization; Scheduling; Construction management.

The Superiority and Inferiority Ranking (SIR) method, a multicriteria decision-making technique, is proposed for facilitating the process of construction plant selection. The SIR method draws together the strengths of most multicriteria decision-making models in handling nonquantifiable, cardinal, and/or ordinal data and allows imprecise information by introducing concepts like indifference and preference thresholds for each criterion. In addition, the technique is capable of dealing with data in different units. The application of the SIR method is illustrated with a case study in the evaluation of l0 alternative concrete pumps based upon nine decision criteria. From the case study, the benefits and strengths of the SIR method in the selection process are unveiled. DOI: 10.1061/(ASCE)0733-9364(2004)130:6(827) CE Database subject headings: Decision making; Construction industry; Hong Kong; Pumps.

The increasing awareness of environmental impacts from construction wastes has led to the development of waste management as an important function of construction project management. Various approaches for managing construction wastes have been developed in the existing research works and practices, and these works can be grouped largely into three areas: waste classification, waste management strategies (avoiding waste, reducing waste, reusing waste, and recycling waste), and waste disposal technologies. Nevertheless, these approaches give less attention to the management of the waste handling process on construction sites. In fact, construction wastes pass through a number of processes from generation to final disposal, and proper flow of these processes can improve waste management effectiveness. This paper examines the waste handling process during construction through mapping six cases selected in Hong Kong construction, with the assistance of the free-flow mapping presentation technique. The examination leads to developing a waste management mapping model (WMMM), which incorporates the good operations embodied in the existing practices. The WMMM provides an alterative tool assisting in planning waste management procedures on construction sites. It can serve as a vehicle for comparing the waste management practices between construction sites, thus both good practices and weak areas can be identified. CE Database subject headings: Construction industry; Construction sites; Waste management; Hong Kong; Mapping.

Site layout planning can affect productivity and is crucial to project success. However, as construction is heterogeneous in the nature of its organizations, project designs, time constraints, environmental effects, etc., site layout planning for each project becomes unique. Affected by many uncertainties (variables) and variations, site layout planning is a typical multiobjective problem. To facilitate the decision-making process for these problems, a nonstructural fuzzy decision support system (NSFDSS) is proposed. NSFDSS integrates both experts' judgment and computer decision modeling, making it suitable for the appraisal of complicated construction problems. The system allows assessments based on pairwise comparisons of alternatives using semantic operators that can provide a reliable assessment result even under the condition of insufficient precise information. DOI: 10.1061/(ASCE)0733-9364(2002)128:3(220) CE Database keywords: Decision support systems; Fuzzy sets; Site preparation, construction.

Accurate assessment of hoisting times is crucial for planning construction activities. The objective of this paper is to develop reasonably accurate prediction models to assess hoisting times of tower cranes. Twenty variables considered attributable to the hoisting time are evaluated. In modeling the hoisting movements, the upward hoisting and downward hoisting of a hoisting cycle are classified as the supply hoisting and the return hoisting. Multiple regression techniques are used for analyzing and building up the models. The hoisting of precast concrete facades and concrete skips are studied. The significance of the variables are discussed and compared. Finally, the paper presents an example of applying the models.