AbstractIn the last 20 years many multi‐objective linear programming (MOLP) methods with continuous variables have been developed. However, in many real‐world applications discrete variables must be introduced. It is well known that MOLP problems with discrete variables can have special difficulties and so cannot be solved by simply combining discrete programming methods and multi‐objective programming methods.The present paper is intended to review the existing literature on multi‐objective combinatorial optimization (MOCO) problems. Various classical combinatorial problems are examined in a multi‐criteria framework. Some conclusions are drawn and directions for future research are suggested.