A stochastic chance constraint-based model for a project supply management (A metaheuristic method)

In today's era, organizations recognize the challenges of meeting the evolving needs and preferences of customers. simply im-proving products and individual performance is insufficient to satisfy customer requirements. instead, organizations have em-braced a collaborative strategy, utilized efficient supply chains and leveraged each other's expertise and resources to enhance customer satisfaction. this approach has been made possible by technological advancements. the literature review identifies two research gaps: insufficient consideration of inherent uncertainty in construction projects and inadequate attention to the multi-objective and multimodal nature of construction project models. to address uncertainties in construction projects, this study employed the chance-constrained programming approach. uncertainty-related parameters were identified and integrated into an optimization model. the primary objective of this study is to minimize project implementation delays. to achieve this, we employ exact algorithms for small and medium-scale problems and utilize nsgaii for large-scale scenarios. our research em-phasizes the critical importance of efficient project timing, cost optimization, and proactive delay management for achieving successful project outcomes. the study reveals critical insights into the impact of resource allocation on the first objective func-tion. the findings show 20% increase in resources for the first activity (i) raises the objective function to 310 units, while a 30% reduction in activity i's completion time lowers it to 188 units. these findings offer valuable benchmarks for decision-making and project optimization. managers can use these insights to enhance decision-making, optimize resource allocation, and ensure timely project completion while maintaining quality and cost control.