997 resultados para Project Scheduling


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A construction project is a group of discernible tasks or activities that are conduct-ed in a coordinated effort to accomplish one or more objectives. Construction projects re-quire varying levels of cost, time and other resources. To plan and schedule a construction project, activities must be defined sufficiently. The level of detail determines the number of activities contained within the project plan and schedule. So, finding feasible schedules which efficiently use scarce resources is a challenging task within project management. In this context, the well-known Resource Constrained Project Scheduling Problem (RCPSP) has been studied during the last decades. In the RCPSP the activities of a project have to be scheduled such that the makespan of the project is minimized. So, the technological precedence constraints have to be observed as well as limitations of the renewable resources required to accomplish the activities. Once started, an activity may not be interrupted. This problem has been extended to a more realistic model, the multi-mode resource con-strained project scheduling problem (MRCPSP), where each activity can be performed in one out of several modes. Each mode of an activity represents an alternative way of combining different levels of resource requirements with a related duration. Each renewable resource has a limited availability for the entire project such as manpower and machines. This paper presents a hybrid genetic algorithm for the multi-mode resource-constrained pro-ject scheduling problem, in which multiple execution modes are available for each of the ac-tivities of the project. The objective function is the minimization of the construction project completion time. To solve the problem, is applied a two-level genetic algorithm, which makes use of two separate levels and extend the parameterized schedule generation scheme. It is evaluated the quality of the schedules and presents detailed comparative computational re-sults for the MRCPSP, which reveal that this approach is a competitive algorithm.

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This paper presents a genetic algorithm for the resource constrained multi-project scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a heuristic that builds parameterized active schedules based on priorities, delay times, and release dates defined by the genetic algorithm. The approach is tested on a set of randomly generated problems. The computational results validate the effectiveness of the proposed algorithm.

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This paper presents a genetic algorithm-based approach for project scheduling with multi-modes and renewable resources. In this problem activities of the project may be executed in more than one operating mode and renewable resource constraints are imposed. The objective function is the minimization of the project completion time. The idea of this approach is integrating a genetic algorithm with a schedule generation scheme. This study also proposes applying a local search procedure trying to yield a better solution when the genetic algorithm and the schedule generation scheme obtain a solution. The experimental results show that this algorithm is an effective method for solving this problem.

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The resource constrained project scheduling problem (RCPSP) is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. During the last couple of years many heuristic procedures have been developed for this problem, but still these procedures often fail in finding near-optimal solutions. This paper proposes a genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities and delay times of the activities are defined by the genetic algorithm. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.

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- The resource constrained project scheduling problem (RCPSP) is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. During the last couple of years many heuristic procedures have been developed for this problem, but still these procedures often fail in finding near-optimal solutions. This paper proposes a genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities and delay times of the activities are defined by the genetic algorithm. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm

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This paper presents a biased random-key genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. Active schedules are constructed using a priority-rule heuristic in which the priorities of the activities are defined by the genetic algorithm. A forward-backward improvement procedure is applied to all solutions. The chromosomes supplied by the genetic algorithm are adjusted to reflect the solutions obtained by the improvement procedure. The heuristic is tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.

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This paper presents a genetic algorithm for the multimode resource-constrained project scheduling problem (MRCPSP), in which multiple execution modes are available for each of the activities of the project. The objective function is the minimization of the construction project completion time. To solve the problem, is applied a two-level genetic algorithm, which makes use of two separate levels and extend the parameterized schedule generation scheme by introducing an improvement procedure. It is evaluated the quality of the schedule and present detailed comparative computational results for the MRCPSP, which reveal that this approach is a competitive algorithm.

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This paper presents a genetic algorithm for the Resource Constrained Project Scheduling Problem (RCPSP). The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities of the activities are defined by the genetic algorithm. The heuristic generates parameterized active schedules. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.

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The authors propose a mathematical model to minimize the project total cost where there are multiple resources constrained by maximum availability. They assume the resources as renewable and the activities can use any subset of resources requiring any quantity from a limited real interval. The stochastic nature is inferred by means of a stochastic work content defined per resource within an activity and following a known distribution and the total cost is the sum of the resource allocation cost with the tardiness cost or earliness bonus in case the project finishes after or before the due date, respectively. The model was computationally implemented relying upon an interchange of two global optimization metaheuristics – the electromagnetism-like mechanism and the evolutionary strategies. Two experiments were conducted testing the implementation to projects with single and multiple resources, and with or without maximum availability constraints. The set of collected results shows good behavior in general and provide a tool to further assist project manager decision making in the planning phase.

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The Iowa Department of Transportation (IDOT) has been requiring Critical Path Method (CPM) schedules on some larger or more schedule sensitive projects. The Office of Construction's expectations for enhanced project control and improved communication of project objectives have not been fully met by the use of CPM. Recognizing that the current procedures might not be adequate for all projects, IDOT sponsored a research project to explore the state-of-the-art in transportation scheduling and identify opportunities for improvement. The first phase of this project identified a technique known as the Linear Scheduling Method (LSM) as an alternative to CPM on certain highway construction projects. LSM graphically displays the construction process with respect to the location and the time in which each activity occurs. The current phase of this project was implemented to allow the research team the opportunity to evaluate LSM on all small groups of diverse projects. Unlike the first phase of the project, the research team was closely involved in the project from early in the planning phase throughout the completion of the projects. The research strongly suggests that the linear scheduling technique has great potential as a project management tool for both contractors and IDOT personnel. However, before this technique can become a viable weapon in the project management arsenal, a software application needs to be developed. This application should bring to linear scheduling a degree of functionality as rich and as comprehensive as that found in microcomputer based CPM software on the market today. The research team recommends that the IDOT extend this research effort to include the development of a linear scheduling application.

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This report proposes, that for certain types of highway construction projects undertaken by the Iowa Department of Transportation, a scheduling technique commonly referred to as linear scheduling may be more effective than the Critical Path Method scheduling technique that is currently being used. The types of projects that appear to be good candidates for the technique are those projects that have a strong linear orientation. Like a bar chart, this technique shows when an activity is scheduled to occur and like a CPM schedule it shows the sequence in which activities are expected to occur. During the 1992 construction season, the authors worked with an inlay project on Interstate 29 to demonstrate the linear scheduling technique to the Construction Office. The as-planned schedule was developed from the CPM schedule that the contractor had developed for the project. Therefore, this schedule represents what a linear representation of a CPM schedule would look like, and not necessarily what a true linear schedule would look like if it had been the only scheduling technique applied to the project. There is a need to expand the current repertoire of scheduling techniques to address those projects for which the bar chart and CPM may not be appropriate either because of the lack of control information or due to overly complex process for the actual project characteristics. The scheduling approaches used today on transportation projects have many shortcomings for properly modeling the real world constraints and conditions which are encountered. Linear project's predilection for activities with variable production rates, a concept very difficult to handle with the CPM, is easily handled and visualized with the linear technique. It is recommended that work proceed with the refinement of the method of linear scheduling described above and the development of a microcomputer based system for use by the Iowa Department of Transportation and contractors for its implementation. The system will be designed to provide the information needed to adjust schedules in a rational understandable method for monitoring progress on the projects and alerting Iowa Department of Transportation personnel when the contractor is deviating from the plan.