OPTIMIZING CONSTRUCTION SCHEDULING USING ARTIFICIAL INTELLIGENCE AND CONSTRAINT PROGRAMMING

The construction industry has always been one of the largest and most complex industries, with numerous challenges in terms of scheduling and project management. Due to its complexity, traditional scheduling methods are often inadequate, leading to delays, over costing, and low productivity. However, recent advances in artificial intelligence (AI) and constraint programming have opened up new opportunities for optimizing construction scheduling. In this research paper, we explore the potential of using AI and constraint programming to optimize construction scheduling, and we present a case study of a real-world construction project to demonstrate the effectiveness of this approach. We conclude by discussing the prospects of AI. The required for the control of schedules is the implementation of the AI-valued approach and AI management to the study of scheduled variation and case-based logic to the development of departure controls. The approach presented in this work may be broadly applicable to a variety of research topics. The methodology may be applied equally to many projects in various disciplines; they just need to create case bases and measure bases appropriate to their professions. It takes a lot of effort to create optimised timetables for building projects. Several execution constraints, circumstances, and needs, such as technological dependencies or resource availability, must be taken into account for each building task. This results in potential execution orders and, as a result, a challenging optimisation challenge. AI comes close to the ideal outcome. The AI methodology and its application are detailed in depth in the sections that follow. Furthermore, a scheduling example for construction is used to illustrate how AI is applied for solving problem based on constraint programming (CP).