Abstract: The progress monitoring method is based on a critical path method (CPM) and conducts comparisons against multiple possible outcomes utilizing neural networks that classify planned progress at specified cut-off dates during a planning stage. The classifications are used to monitor and evaluate actual progress during the construction stage. The pattern recognition techniques generalize a virtual benchmark to represent planned progress based on multiple possible outcomes generated at each cut-off date. The generalization feature overcomes the problem of variation in the quality of data collected. Patterns are constructed to encode planned and actual progress at different cut-off dates. Patterns are readily manipulated within computer programs and substitute for photographs, which are not comprehensive in representing the work status of interior and hidden parts of the under-construction facilities.

Abstract: The method of repairing financially infeasible genetic algorithm chromosome encoding activity start times in scheduling problems 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 on 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. Thus, the algorithm introduces effective chromosomes that maximize the utilization of the available funds and minimize project duration.

Abstract: The progress monitoring method is based on a critical path method (CPM) and conducts comparisons against multiple possible outcomes utilizing neural networks that classify planned progress at specified cut-off dates during a planning stage. The classifications are used to monitor and evaluate actual progress during the construction stage. The pattern recognition techniques generalize a virtual benchmark to represent planned progress based on multiple possible outcomes generated at each cut-off date. The generalization feature overcomes the problem of variation in the quality of data collected. Patterns are constructed to encode planned and actual progress at different cut-off dates. Patterns are readily manipulated within computer programs and substitute for photographs, which are not comprehensive in representing the work status of interior and hidden parts of the under-construction facilities.

Abstract: a method and apparatus is disclosed for scheduling construction projects based on the available finance using integer programming. This method renders CPM/PERT schedules of construction projects executable using bank overdrafts of specified credit limits. Conveniently, the method is organized in three stages; input preparation, schedule extension, and model formulation. Input preparation stage supports preparing CPM/PERT schedule and financial data of the project. Schedule extension stage supports developing a scheme for schedule extension. The scheme is a framework of the original schedule that allows a definite extension increment in the critical path of the CPM. Model formulation stage supports building an integer programming model for the scheme and involves the components of formulating an objective function, setting constraints, and searching for a model solution.

Abstract: a method and apparatus is disclosed for scheduling construction projects based on the available finance using integer programming. This method renders CPM/PERT schedules of construction projects executable using bank overdrafts of specified credit limits. Conveniently, the method is organized in three stages; input preparation, schedule extension, and model formulation. Input preparation stage supports preparing CPM/PERT schedule and financial data of the project. Schedule extension stage supports developing a scheme for schedule extension. The scheme is a framework of the original schedule that allows a definite extension increment in the critical path of the CPM. Model formulation stage supports building an integer programming model for the scheme and involves the components of formulating an objective function, setting constraints, and searching for a model solution.