Building multi-objective multimodal AI system by bi-symmetrical weighted distance project management
Abstract
This study proposes a Bi-symmetrical Weighted Distance (BWD) optimization framework for multimodal AI system development under uncertainty. By integrating fuzzy multi-objective linear programming with possibilistic programming, the approach simultaneously minimizes development costs, deployment time, and acceleration costs. The BWD method effectively handles imprecise parameters through distance-based defuzzification, enhancing decision transparency in intelligent hyperautomation contexts. An industrial case study validates the methodology, demonstrating practical capability to navigate trade-offs among time, cost, and resources where traditional methods struggle with uncertain parameter relationships.
Fields of Study & Subjects
Resource-Constrained Project Scheduling
Constraint Satisfaction and Optimization
Construction Project Management and Performance
Publication details
- Journal / source
- Enterprise Information Systems
- Publisher
- Informa UK Limited
- Volume
- 20
- Issue
- 5-6
- Publication date
- 6 May 2026
- Language
- EN