THE RESOURCE LEVELING PROBLEM WITH MULTIPLE RESOURCES USING AN ADAPTIVE GENETIC ALGORITHMPonz-Tienda, J.L.Yepes, V.Pellicer, E.Moreno-Flores, J. Title Page THE RESOURCE LEVELING PROBLEM WITH MULTIPLE RESOURCES USING AN ADAPTIVE GENETIC ALGORITHM AbstractResources management ensures that a project is completed on time and at cost, and that its quality is as previously defined; nevertheless, resources are scarce and their use in the activities of the project leads to conflicts in the schedule. Resource leveling problems consider how to make the resource consumption as efficient as possible. This paper presents a new Adaptive Genetic Algorithm for the Resource Leveling Problem with multiple resources, and its novelty lies in using the Weibull distribution to establish an estimation of the global optimum as a termination condition. The extension of the project deadline with a penalty is allowed, avoiding the increase in the project criticality punishing the shift of activities. The algorithm is tested with the standard Project Scheduling Problem Library PSPLIB, and a complete analysis and benchmarking test instances are presented. The proposed algorithm is implemented using VBA for Excel 2010 in order to provide a flexible and powerful decision support system that enables practitioners to choose between different feasible solutions to a problem, and in addition it is easily adjustable to the constraints and particular needs of each project in realistic environments.

The evaluation of BIM capabilities and repeatability enables a company or project to identify its current status and how to improve continuously; this evaluation can be performed with BIM maturity models. However, these maturity models can measure the BIM state but not specifically the application of BIM uses. Likewise, in interorganizational project teams with a diversity of factors from various companies, it is possible to evaluate the capacity at a specified time with specified factors, but it is not possible to evaluate the repeatability unless the client always works with the same project teams. Therefore, despite the existence of various BIM uses in the literature, there is no instrument to evaluate the level of implementation of them in construction projects. This research proposes a BIM Use Assessment (BUA) tool for characterizing the levels of application of the BIM uses in the planning and design phases of building projects. The research methodology was organized into three stages: (1) identification, selection, and definition of BIM uses; (2) proposal of the BUA tool for characterizing the level of BIM use application; and (3) validation of the BUA tool. The tool was validated using 25 construction projects, where high reliability and concordance were observed; hence, the BUA tool complies with the consistency and concordance analysis for assessing uses in the design and planning phases of construction projects. The assessment will enable self-diagnosis, stakeholder qualification/selection, and industry benchmarking.

The efficient use of resources is a key factor to minimize the cost while meeting time deadlines and quality requirements; this is especially important in construction projects where field operations make fluctuations of resources unproductive and costly. Resource Leveling Problems (RLP) aim to sequence the construction activities that maximize the resource consumption efficiency over time, minimizing the variability. Exact algorithms for the RLP have been proposed throughout the years to offer optimal solutions; however, these problems require a vast computational capability (“combinatorial explosion”) that makes them unpractical. Therefore, alternative heuristic and metaheuristic algorithms have been suggested in the literature to find local optimal solutions, using different libraries to benchmark optimal values; for example, the Project Scheduling Problem LIBrary for minimal lags is still open to be solved to optimality for RLP. To partially fill this gap, the authors propose a Parallel Branch and Bound algorithm for the RLP with minimal lags to solve the RLP with an acceptable computational effort. This way, this research contributes to the body of knowledge of construction project scheduling providing the optimums of 50 problems for the RLP with minimal lags for the first time, allowing future contributors to benchmark their heuristics methods against exact results by obtaining the distance of their solution to the optimal values. Furthermore, for practitioners, the time required to solve this kind of problem is reasonable and practical, considering that unbalanced resources can risk the goals of the construction project.

In construction projects, resource availability might limit the implementation of ideal schedules. Especially, when repetitive activities are involved, traditional resource‐constrained project scheduling problem (RCPSP) models fail to allocate the resource consumption in an efficient manner. Besides, actual models only provide local optimal solutions and do not incorporate activity acceleration routines. To fulfill this gap, partially, a mathematical optimization model, the multimode RCPSP for repetitive activities in construction projects, is proposed and solved to optimality; it takes into account acceleration routines under real construction scenarios using spreadsheets. The article shows a complete computational experimentation over a real construction project, considering several scenarios of resource availabilities and continuity conditions. The model allows analyzing the resources efficiency indexes comparing them to resource consumptions, continuity of activities, and objective functions that reveal that fragmented activities do not provide better resource efficiency outcomes.

Abstract:In scheduling, estimations are affected by the imprecision of limited information on future events, and the reduction in the number and level of detail of activities. Overlapping of processes and activities requires the study of their continuity, along with analysis of the risks associated with imprecision. In this line, this paper proposes a fuzzy heuristic model for the Project Scheduling Problem with flows and minimal feeding, time and work Generalized Precedence Relations with a realistic approach to overlapping, in which the continuity of processes and activities is allowed in a discretionary way. This fuzzy algorithm handles the balance of process flows, and computes the optimal fragmentation of tasks, avoiding the interruption of the critical path and reverse criticality. The goodness of this approach is tested on several problems found in the literature; furthermore, an example of a 15-story building was used to compare the better performance of the algorithm implemented in Visual Basic for Applications (Excel) over that same example input in Primavera© P6 Professional V8.2.0, using five different scenarios.

The resource leveling problem (RLP) aims to provide the most efficient resource consumption as well as minimize the resource fluctuations without increasing the prescribed makespan of the construction project. Resource fluctuations are impractical, inefficient and costly when they happen on construction sites. Therefore, previous research has tried to find an efficient way to solve this problem. Metaheuristics using Harmony Search seem to be faster and more efficient than others, but present the same problem of premature convergence closing around local optimums. In order to diminish this issue, this study introduces an innovative Improved and Adaptive Harmony Search (IAHS) algorithm to improve the solution of the RLP with multiple resources. This IAHS algorithm has been tested with the standard Project Scheduling Problem Library for four metrics that provide different levelled profiles from rectangular to bell shapes. The results have been compared with the benchmarks available in the literature presenting a complete discussion of results. Additionally, a case study of 71 construction activities contemplating the widest possible set of conditions including continuity and discontinuity of flow relationships has been solved as example of application for real life construction projects. Finally, a visualizer tool has been developed to compare the effects of applying different metrics with an app for Excel. The IAHS algorithm is faster with better overall results than other metaheuristics. Results also show that the IAHS algorithm is especially fitted for the Sum of Squares Optimization metric. The proposed IAHS algorithm for the RLP is a starting point in order to develop user-friendly and practical computer applications to provide realistic, fast and good solutions for construction project managers.

Ключевые слова: Управление освоенной длительностью (EDM), Управление освоенным объемом (EVM), Управление освоенным объ-емом по фазам (PEVM), Управление освоенным графиком (ESM)Для цитирования: Дашков Р. Ю., Тисленко А. В. Система мониторинга и контроля деятельности заинтересованных сторон проекта на основе метода Управления освоенной длительностью // МИР (Модернизация. Инновации. Развитие). 2018. Т. 9. № 1. С. 86-97.

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