The CSPs are fundamental computational problems which consist of a set of variables, an associated set of domains, and a number of constraints or limitations. Map coloring problems, Sudoku, and puzzles are known simple examples which can be modeled as a constraint satisfaction problem.
Although, timetabling problems can be defined as a constraint satisfaction problem,too.
A Multi-Objective Combinatorial Optimization Problem (MOCOP) is defined as a decision problem with more than one objectives which should be optimized (minimized or maximized) simultaneously in consideration with the constraints. In this kind of problems, Unlike single-objective optimization, the solution of a MOCOP is not unique, but is composed instead of a set of solutions representing the best possible trade-offs among the objectives. Such solutions are contained in the so-called Pareto optimal set (PO).
The TTPs are generally tackled as a single-objective optimization problem. Only in recent years, a few Multi-objective optimization TTP problems are investigated in the literature.
Here are some articles about single-objective and multi-objective TTPs:
Conference Paper Solving class timetabling problem of IIT-Kanpur using multi-...
Conference Paper Solving the Exam Timetabling Problem via a Multi-Objective E...
Chapter An Introduction to Multiobjective Metaheuristics for Schedul...
each CSP is just like a puzzle game with puzzle pieces (objects) and different domains (see the 1st link below), but the MOCOPs are decision problems which have multiple objective functions not objects (see the second article).