Optimal Charge Planning Model of Steelmaking Based on Multi-Objective Evolutionary Algorithm

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Multi-Objective Coil Route Planning System for the Steelmaking Industry Based on Evolutionary Algorithms

In this paper a novel route planning system for steel coils that must pass through different processing steps of a generic steelmaking plant will be presented. Production times and costs are often the only considered indicators by traditional planning systems, while, with this newly proposed approach, customers’ quality requirements are also taken into account. In facts, in medium/large steelma...

متن کامل

Solving ‎‎‎Multi-objective Optimal Control Problems of chemical ‎processes ‎using ‎Hybrid ‎Evolutionary ‎Algorithm

Evolutionary algorithms have been recognized to be suitable for extracting approximate solutions of multi-objective problems because of their capability to evolve a set of non-dominated solutions distributed along the Pareto frontier‎. ‎This paper applies an evolutionary optimization scheme‎, ‎inspired by Multi-objective Invasive Weed Optimization (MOIWO) and Non-dominated Sorting (NS) strategi...

متن کامل

An Evolutionary Multi-objective Discretization based on Normalized Cut

Learning models and related results depend on the quality of the input data. If raw data is not properly cleaned and structured, the results are tending to be incorrect. Therefore, discretization as one of the preprocessing techniques plays an important role in learning processes. The most important challenge in the discretization process is to reduce the number of features’ values. This operat...

متن کامل

Optimal Multi-Objective Planning of Distribution System with Distributed Generation

This paper presents a multi-objective formulation for optimal siting and sizing of distributed generation (DG) resources in distribution systems in order to minimize the cost of power losses and energy not supplied. The implemented technique is based on a genetic algorithm (GA) and weight method that employed to obtain the best compromise between these costs. Simulation results on 33-bus distri...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Metals

سال: 2018

ISSN: 2075-4701

DOI: 10.3390/met8070483