In this paper, a new method is proposed to optimize a multi-response optimization problem based on the Taguchi method for the processes where controllable factors are the smaller-the-better (STB)-type variables and the analyzer desires to find an optimal solution with smaller amount of controllable factors. In such processes, the overall output quality of the product should be maximized while t...

in this paper, we considered solving approaches to flexible job shop problems. makespan is not a good evaluation criterion with overlapping in operations assumption. accordingly, in addition to makespan, we used total machine work loading time and critical machine work loading time as evaluation criteria. as overlapping in operations is a practical assumption in chemical, petrochemical, and gla...

Nowadays, demand response programs (DRPs) play an important role in price reduction and reliability improvement. In this paper, an optimal integrated model for the emergency demand response program (EDRP) and dynamic economic emission dispatch (DEED) problem has been developed. Customer’s behavior is modeled based on the price elasticity matrix (PEM) by which the level of DRP is determined for ...

Human error is a significant and ever-growing problem in the healthcare sector. In this study, resource allocation problem is considered along with human errors to optimize utilization of resources in an emergency department. The algorithm is composed of simulation, artificial neural network (ANN), design of experiment (DOE) and fuzzy data envelopment analysis (FDEA). It is a multi-response opt...

Most of existing researches for multi response optimization are based on regression analysis. However, the artificial neural network can be applied for the problem. In this paper, two approaches are proposed by consideration of both methods. In the first approach, regression model of the controllable factors and S/N ratio of each response has been achieved, then a fuzzy programming has been app...

This chapter presents the application of a comprehensive statistical analysis for both algorithmic performance comparison and optimal parameter estimation on a multi-objective digital signal processing problem. The problem of designing optimum digital finite impulse response (FIR) filters with the simultaneous approximation of the filter magnitude and phase is posed as a multiobjective optimiza...

A decision making process requires the values of conflicting objectives for alternatives and the selection of the best alternative according to the needs of decision makers. Multi-objective optimization methods may provide solution for this selection. In this paper it is aimed to present the laptop selection problem based on MOORA plus full multiplicative form (MULTIMOORA) and multi-objective o...

Introduction/purpose: Researchers of fluids for high voltage engineering application always experience problems when selecting and recommending specific suitable application. This is due to the dual functionality required equipment. Methods: study introduced employed a probability-based multi-objective optimization technique in selection thermofluids. Beneficial unbeneficial preferable probabil...

in this paper, a multi purpose function is presented for optimum design in circular hydrostatic axial bearings. one or more parameters that are directly or indirectly dependent on given data are optimized. usually in the local optimization methods, it is not possible to optimize several parameters simultaneously. in this research, simultaneous optimization of the power loss and the oil temperat...