In this paper, a globally convergent Newton-type proximal gradient method is developed for composite multi-objective optimization problems where each objective function can be represented as the sum of smooth and nonsmooth function. The proposed deals with unconstrained convex problems. This free from any kind priori chosen parameters or ordering information functions. At every iteration method...

This paper presents a wide-range routing method for multiple rovers deployed lunar polar exploration mission. In the mission scenario considered in this paper, points are divided into several sets of to be assigned rovers. Subsequently, routes between generated each rover. assignment and problems well known as Traveling Salesman Problem (mTSP). The aims minimize two objective functions: sum sta...

Multi-Objective Optimization takes care of different objectives with the objectives keeping their own units. The internal mechanical solution of a Ratio System, producing dimensionless numbers, is preferred. The ratio system creates the opportunity to use a second approach: a Reference Point Theory, which uses the ratios of the ratio system. This overall theory is called MOORA (Multi-Objective ...

Inference of gene regulatory networks (GRNs) based on experimental data is a challenging task in bioinformatics. In this paper, we present a biobjective minimization model (BoMM) for inference of GRNs, where one objective is the fitting error of derivatives, and the other is the number of connections in the network. To solve the BoMM efficiently, we propose a multi-objective evolutionary algori...

A numerical method is proposed for constructing an approximation of the Pareto front of nonconvex multi-objective optimal control problems. First, a suitable scalarization technique is employed for the multi-objective optimal control problem. Then by using a grid of scalarization parameter values, i.e., a grid of weights, a sequence of single-objective optimal control problems are solved to obt...

The operational aspects of power systems pose some of the most challenging problems encountered in the restructuring of electric power industry. This paper focuses on Congestion Management within an Optimal Power Flow (OPF) framework in the deregulated electricity market scenario. The conventional OPF problem is modified to create a mechanism that enables the market players to compete and trade...