chance constraint programming

In today's era, organizations recognize the challenges of meeting the evolving needs and preferences of customers. Simply improving products and individual performance is insufficient to satisfy customer requirements. Instead, organizations have embraced 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 inade-quate 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 parame-ters 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 emphasizes the critical importance of efficient project timing, cost optimi-zation, and proactive delay management for achieving successful project outcomes. The study reveals critical insights into the impact of resource allocation on the first objective function. 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.

This paper presents a novel multi-objective location arc-routing model in order to locate disposal facilities and to design optimal routes of residential waste taking into consideration many complicated real constraints such as a heterogeneous fleet of vehicles, time windows for customers, disposal facilities and the depot, capacities for vehicles and facilities. The first objective is the minimization of transportation costs, including service costs and fuel costs of vehicles. The second one minimizes total number of utilized vehicles. And finally, the third objective function is considered for minimizing total number of established disposal centers. Moreover, to come closer to reality the service time, amount of demands, capacities and cost parameters are considered as fuzzy ones. To solve the proposed model, a credibility-based fuzzy mathematical model and its interactive solution method with three recent approaches, are used and the results are compared with each other.