This paper develops an integrated decision-making framework for tender evaluation and subcontractor selection in construction projects. The framework responds to the limitations of lowest-bid procurement by combining prequalification, Data Envelopment Analysis (DEA), fuzzy logic assessment, Fuzzy TOPSIS prioritization, and bi-objective Mixed-Integer Linear Programming (MILP). In the first stage, DEA screens subcontractors and retains only efficient candidates. In the second stage, risk and environmental exposure factors are evaluated using linguistic judgments and fuzzy logic. Fuzzy TOPSIS is used as a supporting prioritization check to compare ordering of efficient subcontractors under multiple criteria. In the final stage, a bi-objective MILP model selects the subcontractor or subcontractors and determines the quantity of work assigned to each selected subcontractor by minimizing total cost and total risk. A numerical UAE construction tendering case application demonstrates how the framework supports transparent award decisions and helps tender committees evaluate cost-risk trade-offs before contract award.