Multi-objective programming is commonly used in the literature when conflicted objectives
arise in solving optimization problems. Over the past decades, classical optimization …

Artificial neural networks or neural networks (NN) are new computational models based on
the working of biological neurons of human body. A NN model consists of an interactive …

This bibliography of fractional programming is a continuation of eight previous
bibliographies by the author (Pure Appl. Math. Sci.(India), Vol. XIII, No. 1–2, 35–69, March …

This paper addresses the general fully neutrosophic multi-level multiobjective programming
problems ie. ML-MOLPPs in which not only coefficients of each objective at each level but …

This study first surveys fuzzy linearization approaches for solving multi-objective linear
fractional programming (MOLFP) problems. In particular, we review different existing …

This paper describes solution methodology for bi-level multiobjective programming
problems (BL-MOPPs) with interval-valued trapezoidal neutrosophic numbers (IVTrNNs) …

In this work, necessary optimality conditions of KKT type for (weak) Pareto optimality are
derived and a DC-Dinkelbach-type algorithm is proposed for vector fractional mathematical …

This study presents a hybrid algorithm consisting of game theory and the first order Taylor
series approach to find compromise solutions to multi-objective linear fractional …

In this paper, we provide a new scheme for approximating the weakly efficient solution set
for a class of vector optimization problems with rational objectives over a feasible set defined …

Mathematical programming problems (MPPs) having unique mathematical format usually
treated as hard problems are important optimization problems. On the other hand, particle …