Optimization of the whole plant instead of important individual units is essential for maximizing savings and operational efficiency. Often, there are conflicting objectives for optimizing industrial processes. Many previous studies on multi-objective optimization involved a few critical units (and not complete plants) using models and simulation programs specifically developed for the respecti...

In this study, a bi-objective optimization model was established to solve the cooperative distribution problem of multi-center hybrid fleet by integrating reverse logistics under real-time road conditions. According characteristics and considering power level battery capacity electric vehicles, multi-objective immune genetic algorithm (MOIGA) designed compared with an elitist strategy algorithm...

The non-dominated sorting genetic algorithm II (NSGA-II) is the most intensively used multi-objective evolutionary (MOEA) in real-world applications. However, contrast to several simple MOEAs analyzed also via mathematical means, no such study exists for NSGA-II so far. In this work, we show that runtime analyses are feasible NSGA-II. As particular results, prove with a population size larger t...

The current overall layout planning model matrix of landscape ceramic sculpture is generally unidirectional, and the efficiency low, resulting in a decline optimization ratio model. Therefore, design verification analysis sculpture’s based on Nondominated Sorting Genetic Algorithm (NSGA - II) algorithm proposed. According to actual needs standards, first set basic points, establish cross-planni...

Market-oriented production systems generally have the characteristics of multi-product and small-batch production. Dynamic virtual cellular manufacturing create cells periodically in a planning horizon to respond changing demands flexibly quickly, thus are suitable for problems market-oriented systems. In current research, we propose dynamic cell reconfiguration framework under environment with...

Abstract The flexible job-shop scheduling problem (FJSP) is a critical model in manufacturing systems that assigns operations from different jobs to various machines. However, optimizing multiple targets during the production process always necessary. While non-dominated sorting genetic algorithm (NSGA-II) an effective method solve multi-objective FJSP, it can have main drawbacks of converging ...

A major difficulty in the use of metaheuristics (i.e. evolutionary and particle swarm algorithms) to deal with multi-objective optimization problems is the choice of a convenient point at which to stop computation. Indeed, it is difficult to find the best compromise between the stopping criterion and the algorithm performance. This paper addresses this issue using the Non-dominated Sorting Gene...