Multiobjective Optimization Approaches for Room Allocation in University Course Timetabling✩

This study addresses the complex and time-consuming task of room allocation in university timetabling, which, despite the avail-ability of software tools, is still predominantly performed manually due to the inefficiency of existing solutions. The adoption of such software remains limited, primarily due to complex parameter configurations and the lack of institutional customization. This paper focuses on the room allocation subproblem of the University Course Timetabling Problem (UCTP) and defines six criteria: four objectives to minimize student relocation between buildings, mismatches between requested and assigned room types, waste of room capacity and room changes between consecutive classes, and two hard constraints to ensure that room capacity require-ments are respected and to prevent scheduling overlaps. Customized variants of NSGA-II, NSGA-III, and MOEA/D, tailored to the room allocation context, were developed using the jMetal framework with integrated local search. Experiments were conducted using real-world data from a university over a full academic semester, involving approximately 10,000 students, more than 26,000 scheduled class sessions, and over 120 classrooms distributed across multiple buildings with over 20 distinct room types. The cus-tomized multiobjective evolutionary algorithms were compared against an integer linear programming (ILP) formulation modeled in Pyomo and solved using Gurobi.