Fuzzy Greedy Search: A Deterministic Heuristic for Combinatorial Optimization

This paper presents mathematics of the so-called fuzzy greedy evaluation concept which can be integrated into approaches for hard combinatorial optimization problems. The proposed method evaluates objects in a way that combines fuzzy reasoning with a greedy mechanism, thereby exploiting a fuzzy solution space using greedy methods. Given that the greedy algorithms are computationally inexpensive compared to other more sophisticated methods for combinatorial optimization; this shows practical significance of using the proposed approach. The effectiveness and efficiency of the proposed method are demonstrated on permutation flow-shop scheduling as one of the most widely studied hard combinatorial optimization problems in the area of operational research and management science.