Integrating project management (PM) and sustainable development (SD) is not merely an option but a necessity for smart cities (SC) to secure a prosperous future for the next generations. Also, useful PM plays a vital role in fostering sustainable growth within SC, as it enhances the quality of life, conserves natural resources, and encourages technological creation. Therefore, this study aimed to examine the significance of PM in advancing the SD of SC. Randomly 189 questionnaires were distributed to possible respondents working in PM by email, hardcopy mailings, and web-collection apps. The statistical analysis was carried out using SPSS version 25, by using a quantitative research approach. The results showed that all study variables (smart technologies company policies, resource management, and organizational culture) positively impacted smart cities' SD. Therefore, the study recommends enhancing the incorporation of PM and SD in SC by implementing effective processes and technologies that connect harmoniously with technological advancement and environmental and social sustainability.

The issue of resource over-allocating is a big concern for project engineers in the process of scheduling project activities. Resource over-allocating is frequently seen after initial scheduling of a project in practice and causes significant amount of efforts to modify the initial schedules. In this research, a new method is developed for modifying over-allocated schedules in a multi-mode resource constrained project scheduling problems (MRCPSPs) with positive cash flows (MRCPSP-PCF). The aim is to maximize profit of the MRCPSPs or logically minimizing costs. The proposed method can be used as a macro in Microsoft Office Project® Software to modify resource over-allocated days after scheduling a project. This research considers progress payment method and preemptive resources. The proposed approach maximizes profit by scheduling activities through the resource calendar respecting to the available level of preemptive resources and activity numbers. To examine the performance of the proposed method a number of experiments derived from the literature are solved. The results are then compared with the circumstances where resource constraints are relaxed. The outcomes show that in all studied cases, the proposed algorithm can provide modified schedules with no over-allocated days. Afterward the method is applied to modify a manufacturing project in practice.