A new strategy to approach multiresponse optimization in conjunction to a D-optimal design for simultaneously optimizing a large number of experimental factors is proposed.
This paper presents an investigation into simultaneous optimization of PZT-based actuators by simultaneously optimizing two sets of design variables, i.e., controlling and geometrical parameters for morphing plate structural shapes.
In recent years, the development of multi-objective optimization techniques for simultaneously optimizing multiple and conflicting objectives have received wide attention in the literature.
This study attempts to integrate energy wood harvesting into forest management optimization, and analyses the energy wood harvest from precommercial thinning using a simulation-optimization system for simultaneously optimizing timber and energy wood production.
By using the guaranteed service approach to model the multi-echelon stochastic inventory system, we develop an optimization model for simultaneously optimizing the transportation, inventory and network structure of a multi-echelon supply chain.
This paper presents a methodology based on numerical optimization techniques for simultaneously optimizing design parameters of a two-link planar rigid manipulator and a nonlinear gain PD controller designed for performing multiple tasks.
Multi-goal optimization (also known as multi-objective optimization) is the process of simultaneously optimizing two or more conflicting goals (or objectives) subject to a set of constraints [ 63- 65].
The rule base of the proposed PSO FLC is tuned for optimal control performance by simultaneously optimizing displacement, drift ratio, acceleration and average control force.
Multi-objective optimization is the process of simultaneously optimizing two or more conflicting objectives subject to certain constraints.
The optimal inoculum size was determined simultaneously optimizing the number (amount) of the PUF particles (Table 2) using as a criterion the biomass passively immobilized in the carrier during one single cycle of 240 h.
Presented in this contribution is a formulation that addresses optimization of both water and energy, while simultaneously optimizing the batch process schedule.
