Trip distribution deals with estimation of trips distributed among origins and destinations and is one of the important stages in transportation planning. Since in the real world, trip distribution models often have more than one objective, multi-objective models are developed to cope with a set of conflict goals in this area. In a proposed method of adapted non-dominated sorting algorithm (ANS...

The deployment strategy for wireless sensor networks (WSNs) affects the quality of service (QoS). Adopting a reasonable can improve QoS WSNs. In this paper, problem regarding node WSNs on three-dimensional (3D) terrain is modeled as multi-objective optimization problem. coverage rate WSNs, their unbalanced energy consumption, and number nodes are used fitness functions We propose non-dominated ...

In this article, the multi-objective optimization of cylindrical aluminum tubes under axial impact load is presented.The absorbed energy and the specific absorbed energy (SEA) are considered as objective functions while the maximum crush load should not exceed allowable limit. The geometric dimensions of tubes including diameter, length and thickness are chosen as design variables. The Non-domi...

With the huge global and wide range of attention placed upon quality, promoting and optimize the reliability of the products during the design process has turned out to be a high priority. In this study, the researcher have adopted one of the existing models in the reliability science and propose a bi-objective model for redundancy allocation in the series-parallel systems in accordance with th...

Integrated production-distribution planning (PDP) is one of the most important approaches in supply chain networks. We consider a supply chain network (SCN) to consist of multi suppliers, plants, distribution centers (DCs), and retailers. A bi-objective mixed integer linear programming model for integrating production-distribution designed here aim to simultaneously minimize total net costs in ...

In this paper, we propose an efficient approach to design optimization of analog circuits that is based on the reinforcement learning method. In this work, Multi-Objective Learning Automata (MOLA) is used to design a two-stage CMOS operational amplifier (op-amp) in 0.25μm technology. The aim is optimizing power consumption and area so as to achieve minimum Total Optimality Index (TOI), as a new...

This chapter presents three MS Excel programs, namely, EMOO (Excel based Multi-Objective Optimization), NDS (Non-Dominated Sorting) and PM (Performance Metrics) useful for Multi-Objective Optimization (MOO) studies. The EMOO program is for finding non-dominated solutions of a given MOO problem. It has both binary-coded and realcoded NSGA-II (Elitist Non-Dominated Sorting Genetic Algorithm), and...

In this paper, developed a new multi-product, multi-period, and multi-level closed-loop green supply chain planning model under uncertain conditions. The formulated model consists of five objective functions, which minimize the cost of the supply chain, minimize the CO2 emission of transportation vehicles, maximize the reliability of manufacturing and distribution centers, maximize t...

A multi-objective optimization (MOO) of two-element wing models with morphing flap by using computational fluid dynamics (CFD) techniques, artificial neural networks (ANN), and non-dominated sorting genetic algorithms (NSGA II), is performed in this paper. At first, the domain is solved numerically in various two-element wing models with morphing flap using CFD techniques and lift (L) and drag ...

Ever-increasing energy demand has led to geographic expansion of transmission lines and their complexity. In addition, higher reliability is expected in the transmission systemsdue to their vital role in power systems. It is very difficult to realize this goal by conventional monitoring and control methods. Thus, phasor measurement units (PMUs) are used to measure system parameters. Although in...