Water Permeability of Silica Fume/Cement Mortars

Civil Engineerin

Heuristic method for multi-project finance-based scheduling

A heuristic method is proposed for scheduling multiple projects subject to cash constraints. The heuristic determines cash availability during a given period, identifies all possible activities' schedules, determines the cash requirements for each schedule, ranks schedules based on the contribution to minimizing the increase in the project duration, schedules all activities of the selected schedule and determines the impact of the scheduled activities on the project cash flow. The effectiveness of the heuristic method was validated by comparing the results with the optimum results obtained by using the integer programming (IP) technique for 15 networks comprising up to 60 activities. The comparison indicated that the solutions obtained using the proposed heuristic are very comparable to the optimum solutions. An example of two concurrent projects was presented to demonstrate the proposed heuristic method. The proposed heuristic offers the ultimate flexibility to enter cash outflows and inflows at the actual occurrence time, the ability to rationalize the scheduling process, the flexibility to either devise or update schedules, and the ability to schedule practical-size multiple projects. Finally, this heuristic can be easily coded in software to help managers schedule projects under finance-constrained conditions.Cash flow management, construction finance, financial management, heuristic, scheduling,

Finance-based CPM/LOB scheduling of projects with repetitive non-serial activities

Projects of repetitive non-serial activities constitute a major category of construction projects which can be scheduled more conveniently using the line of balance (LOB) technique. Generally, scheduling activities such that the expenditures are always in balance with the available cash is a must to devise financially feasible schedules. The objective is to integrate a CPM/LOB model for a project of repetitive non-serial activities with a cash flow model and utilize the integrated model to devise financially feasible schedules. The genetic algorithms (GAs) technique is employed to maximize the profit at the end of the project under the constraints of available cash. The optimization of the integrated models was demonstrated using an example project of 15 activities carried out at five units. The CPM/LOB model was validated against the results of a dynamic programming model in the literature and further by conducting a sensitivity analysis of the results of the integrated model. Finally, the model offers an effective financial planning tool for projects of repetitive non-serial activities. © 2009 Taylor & Francis

Progress monitoring of construction projects using pattern recognition techniques

Project monitoring involves collecting the actual‐progress data, and comparing them against the relevant planned‐progress data to evaluate the overall project progress at specified cut‐off dates. Inevitable issues including variations in reporting skills as well as the willingness to record accurate data impact on the quality of the collected data. Comparison against multiple possible benchmarks (one‐to‐many) rather than a single benchmark (one‐to‐one) offers the potential to alleviate the negative impact of low‐quality data on the progress evaluation. Special patterns, which can be readily manipulated within computer programs, are devised to encode the planned and actual progress at the cut‐off dates. Basically, pattern recognition techniques are utilized to classify the multiple patterns representing the planned progress at a given cut‐off date and the classification is used to evaluate the pattern representing the actual progress at the same date. The pattern recognition techniques generalize a virtual benchmark to represent the planned progress based on multiple patterns generated at a given cut‐off date and representing possible benchmarks. In addition to the alleviation of the negative impact of low‐quality data on the progress evaluation, the generalization feature potentially encourages a long‐run attitude in site personnel to report high‐quality data. Finally, the pattern recognition concept and technique proved their robustness to monitor and evaluate the overall progress of the projects based on the technique of critical path method.Progress monitoring, project control, pattern recognition, artificial neural network, statistical models,

Finance‐based CPM/LOB scheduling of projects with repetitive non‐serial activities

Projects of repetitive non‐serial activities constitute a major category of construction projects which can be scheduled more conveniently using the line of balance (LOB) technique. Generally, scheduling activities such that the expenditures are always in balance with the available cash is a must to devise financially feasible schedules. The objective is to integrate a CPM/LOB model for a project of repetitive non‐serial activities with a cash flow model and utilize the integrated model to devise financially feasible schedules. The genetic algorithms (GAs) technique is employed to maximize the profit at the end of the project under the constraints of available cash. The optimization of the integrated models was demonstrated using an example project of 15 activities carried out at five units. The CPM/LOB model was validated against the results of a dynamic programming model in the literature and further by conducting a sensitivity analysis of the results of the integrated model. Finally, the model offers an effective financial planning tool for projects of repetitive non‐serial activities.Scheduling, repetitive construction, genetic algorithms, cash flow management, line of balance,