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A Parallel Branch and Bound Algorithm for the Resource Leveling Problem with Minimal Lags

机译:最小滞后资源均衡问题的并行分支定界算法

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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.
机译:有效利用资源是在满足时间期限和质量要求的同时将成本最小化的关键因素;这在建设项目中尤其重要,因为在这些项目中,野外作业会使资源的波动变得无效且代价高昂。资源均衡问题(RLP)的目的是对建设活动进行排序,以最大程度地提高资源消耗效率,从而最大程度地减少变化。多年来,已经提出了用于RLP的精确算法,以提供最佳解决方案。但是,这些问题需要巨大的计算能力(“组合爆炸”),这使其不切实际。因此,文献中提出了启发式算法和元启发式算法的替代方法,以找到局部最优解,使用不同的库对最优值进行基准测试。例如,对于最小延迟的项目计划问题库仍然是有待解决的,以解决RLP的最优性。为了部分填补这一空白,作者为RLP提出了并行分支定界算法,具有最小的滞后时间,可以用可接受的计算量来求解RLP。这样,这项研究有助于建设项目进度的知识体系,首次为RLP提供了50个问题的最佳选择,且延迟最小,这使未来的贡献者可以通过获得解决方案的距离来针对实际结果对启发式方法进行基准测试达到最佳值。此外,对于从业者来说,解决这种问题所需的时间是合理且实际的,因为不平衡的资源可能会对建设项目的目标造成风险。

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