In this study, we considered a bi-objective, multi-project, multi-mode resource-constrained project scheduling problem. We adopted three objective pairs as combinations of the net present value (NPV) as a financial performance measure with one of the time-based performance measures, namely, makespan (C_max), mean completion time (MCT), and mean flow time (MFT) (i.e., minC_max/maxNPV, minMCT/maxNPV, and minMFT/maxNPV). We developed a hybrid non-dominated sorting genetic algorithm II (hybrid-NSGA-II) as a solution method by introducing a backward–forward pass (BFP) procedure and an injection procedure into NSGA-II. The BFP was proposed for new population generation and post-processing. Then, an injection procedure was introduced to increase diversity. The BFP and injection procedures led to improved objective functional values. The injection procedure generated a significantly high number of non-dominated solutions, thereby resulting in great diversity. An extensive computational study was performed. Results showed that hybrid-NSGA-II surpassed NSGA-II in terms of the performance metrics hypervolume, maximum spread, and the number of non-dominated solutions. Solutions were obtained for the objective pairs using hybrid-NSGA-II and three different test problem sets with specific properties. Further analysis was performed by employing cash balance, which was another financial performance measure of practical importance. Several managerial insights and extensions for further research were presented.

Quality function deployment (QFD) is an effective method that helps companies analyze customer requirements (CRs). These CRs are then turned into product or service characteristics, which are translated to other attributes. With the QFD method, companies could design or improve the quality of products or services close to CRs. To increase the effectiveness of QFD, we propose an improved method based on Pythagorean fuzzy sets (PFSs). We apply an extended method to obtain the group consensus evaluation matrix. We then use a combined weight determining method to integrate former weights to objective weights derived from the evaluation matrix. To determine the exact score of each PFS in the evaluation matrix, we develop an improved score function. Lastly, we apply the proposed method to a case study on assembly robot design evaluation.

Machine intelligence is increasingly entering roles that were until recently dominated by human intelligence. As humans now depend upon machines to perform various tasks and operations, there appears to be a risk that humans are losing the necessary skills associated with producing competitively advantageous decisions. Therefore, this research explores the emerging area of human versus machine decision-making. An illustrative engineering case involving a joint machine and human decision-making system is presented to demonstrate how the outcome was not satisfactorily managed for all the parties involved. This is accompanied by a novel framework and research agenda to highlight areas of concern for engineering managers. We offer that the speed at which new human-machine interactions are being encountered by engineering managers suggests that an urgent need exists to develop a robust body of knowledge to provide sound guidance to situations where human and machine decisions conflict. Human-machine systems are becoming pervasive yet this research has revealed that current technological approaches are not adequate. The engineering insights and multi-criteria decision-making tool from this research significantly advance our understanding of this important area.

The author discusses the application of System Dynamics to high-level strategic simulation in construction. In particular, System Dynamics’ strength on representing feedback processes, aggregation, soft variables, and continuous simulation clock for high-level simulation are discussed using real modeling examples. From this exercise, it is concluded that System Dynamics offers a great potential for strategic simulation in construction. Further, the author proposes a comprehensive simulation framework that integrates System Dynamics and Discrete Event Simulation for a strategic decision making process in construction where operational details should be taken into account.

Drawing on resource dependence theory, this paper develops and empirically tests a model for understanding how the implementation of building information modeling (BIM) in construction projects impacts the performance of different project participating organizations through improving their interorganizational collaboration capabilities. Based on two sets of survey data collected from designers and general contractors in BIM-based construction projects in China, the results from partial least squares analysis and bootstrapping mediation test provide clear evidence that BIM-enabled capabilities of information sharing and collaborative decision-making as a whole play a significant role in determining BIM-enabled efficiency and effectiveness benefits for both designers and general contractors. The results further reveal that designers and general contractors benefit from project BIM implementation activities significantly non-equivalently, and that this non-equivalence closely relates to the different roles played by designers and general contractors in BIM-enabled interorganizational resource exchange processes. The findings validate the resource dependence theory perspective of BIM as a boundary spanning tool to manage interorganizational resource dependence in construction projects, and contribute to deepened understandings of how and why project participating organizations benefit differently from the implementation of interorganizational information technologies like BIM.