Time, cost, and quality are the three indispensable factors for the realization and success of a project. In this context, we propose a framework composed of a multi-objective approach and multi-criteria decision-making methods (MCDM) to solve time-cost-quality trade-off optimization problems. A multi-objective Simulated Annealing (MOSA) algorithm is used to compute an approximation to the Pareto optimal set. The concept of the exploratory grid is introduced in the MOSA to improve its performance. MCDM are used to assist the decision-making process. The Shannon entropy and AHP methods assign weights to criteria. The first methodology is for the inexperienced decision-makers, and the second concedes a personal and flexible weighting of the criteria weights, based on the project manager’s assessment. The TOPSIS and VIKOR methods are considered to rank the solutions. Although they have the same purpose, the rankings achieved are different. A tool is implemented to solve a time-cost-quality trade-off problem on a project activities network. The computational experiments are analyzed and the results with the exploratory grid in Simulated Annealing (SA) are promising. Despite the framework aims to solve multi-objective trade-off optimization problems, supporting the decisions of the project manager, the methodologies used can also be applied in other areas.

中文翻译：

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在多目标模拟退火中使用探索性网格概念的项目管理问题中的时间成本质量优化框架

时间、成本和质量是一个项目的实现和成功不可或缺的三个因素。在这种情况下，我们提出了一个由多目标方法和多标准决策方法（MCDM）组成的框架来解决时间-成本-质量权衡优化问题。多目标模拟退火 (MOSA) 算法用于计算帕累托最优集的近似值。MOSA 中引入了探索性网格的概念以提高其性能。MCDM 用于协助决策过程。香农熵和 AHP 方法为标准分配权重。第一种方法适用于缺乏经验的决策者，第二种方法允许根据项目经理的评估对标准权重进行个人和灵活的加权。TOPSIS 和 VIKOR 方法被认为是对解决方案进行排序。虽然他们的目的相同，但获得的排名却是不同的。实施了一种工具来解决项目活动网络上的时间成本质量权衡问题。对计算实验进行了分析，在模拟退火 (SA) 中使用探索性网格的结果是有希望的。尽管该框架旨在解决多目标权衡优化问题，支持项目经理的决策，但所使用的方法也可以应用于其他领域。对计算实验进行了分析，在模拟退火 (SA) 中使用探索性网格的结果是有希望的。尽管该框架旨在解决多目标权衡优化问题，支持项目经理的决策，但所使用的方法也可以应用于其他领域。对计算实验进行了分析，在模拟退火 (SA) 中使用探索性网格的结果是有希望的。尽管该框架旨在解决多目标权衡优化问题，支持项目经理的决策，但所使用的方法也可以应用于其他领域。