Semantics has become a key topic of research in Genetic Programming (GP). refers to the outputs (behaviour) GP individual when this is run on dataset. The majority works that focus semantic diversity single-objective indicates it highly beneficial evolutionary search. Surprisingly, there minuscule conducted semantics Multi-objective (MOGP). In work we make leap beyond our understanding MOGP and...

One of the main challenges designing effective reverse logistic network is to predict amount product which reach end their useful life. Thus, in this study, we propose fuzzy multi-objective mixed integer linear programming (Fuzzy-MOMILP) model returned considered as an uncertain parameter. In order solve proposed multi objective mathematical model, a solution approach applied. The Fuzzy-MOMILP ...

The traditional frameworks for fuzzy linear optimization problems are inspired by the max–min model proposed by Zimmermann using the Bellman–Zadeh extension principle to aggregate all the fuzzy sets representing flexible (fuzzy) constraints and objective functions together. In this paper, we propose an alternative approach to model fuzzy multi-objective linear programming problems (FMOLPPs) fro...

The traveling salesman problem (TSP) is one of the most intensively studied problems in computational mathematics. Information about real life systems is often available in the form of vague descriptions. Hence, fuzzy methods are designed to handle vague terms, and are most suited to finding optimal solutions to problems with vague parameters. This study develops a fuzzy multi-objective linear ...

Transportation problem is a linear programming which considers minimum cost for shipping a product from some origins to other destinations such as from factories to warehouse, or from a warehouse to supermarkets. To solve this problem simplex algorithmis utilized. In real projects costs and the value of supply and demands are fuzzy numbers and it is expected that optimal solutions for determini...