The global optimization of constrained Non-Linear Bi-Objective Optimization problems (NLBOO) aims at covering their Pareto-optimal front which is in general a manifold in R. Continuation methods can help in this context as they can follow a continuous component of this front once an initial point on it is provided. They constitute somehow a generalization of the classical scalarizing framework ...

ABSTRACT: The problem of robust design is treated as a bi-objective optimization problem in which the performance mean and variation are optimized and minimized, respectively. A method for deriving a utility function as a local approximation of the efficient frontier is presented and investigated at different locations of candidate solutions, with different ranges of interest, and for efficient...

Cost-effective manufacturing processes or products are no longer the only requirements for business sustainability. An approach based on Game Theory is suggested to find solutions bi-objective problems. In particular, Stackelberg’s technique employed and complemented with Factors Scaling tool help users in defining its strategy optimizing process product quality characteristics. No subjective i...

Smart agriculture which integrates the with Internet of Things (IoT) has attracted attention since it contributes to increase productivity and quality crops, reduce energy consumption facilitate farmers. Wireless sensor networks (WSNs) unmanned aerial vehicles (UAVs) are two most commonly deployed devices that used for enabling smart agriculture. In this paper, we design a collaborative WSN-UAV...

For a practical structural health monitoring (SHM) system, the traditional single objective methods for optimal sensor placement (OSP) cannot always obtain result of deployment without sacrificing other targets, which creates obstacles to efficient use sensors. This study mainly focuses on establishing bi-objective optimization method select positions. The significance several single-objective ...

In this paper the multi-mode resource-constrained project scheduling problem with discounted cash flows is considered. Minimizing the makespan and maximization the net present value (NPV) are the two common objectives that have been investigated in the literature. We apply one evolutionary algorithm named multiobjective particle swarm optimization (MOPSO) to find Pareto front solutions. We used...