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Optimization and research of the nonlinear programming model of the full cost of pre-ironmaking under carbon emission reduction constraint

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ENERGY REPORTS 2023年 9卷 2247-2252页

作者： Peng, Haibo Yao, Yaochun Chen, Fugang Zhou, Rong Kunming Univ Sci & Technol Kunming Peoples R China Kunming Iron & Steel Holding Co LTD Kunming Peoples R China Baowu Grp Zhongnan Iron & Steel Co LTD Guangzhou Peoples R China

Under the overall requirements of China's implementation of the "Dual Carbon"strategy and green manufacturing, the iron and steel industry will face severe challenges from carbon emission reduction in addition to costs. Pellet's substitution of sintering is an important measure to effectively reduce the waste gas pollution load of pre-ironmaking, reduce energy consumption and carbon emission reduction, and is an important way for iron and steel industry to move towards green manufacturing. The cost reduction proposed in this paper is not limited to considering the intermediate processes such as procurement, sintering and pelletizing, but the overall consideration of the whole process from raw material procurement to blast furnace production. With the maximum molten iron profit as the objective function, the key factors such as ore inventory, sinter, pellets, molten iron and slag are comprehensively considered, and the mechanism model is established according to the comprehensive consideration of material flow, energy flow and information flow. Through the support of the system, it not only improves the pig iron profit, improves the metallurgical performance of the burden structure and slag performance, and promotes the smooth running of the blast furnace, but also reduces the market risk caused by the concentrate and lump ore inventory in the current period.(c) 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Carbon emission reduction Pellet?s substitution of sintering Pre-ironmaking batching Full cost optimization Operational research nonlinear programming model Intelligent ore blending

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Fabrication of Wood Fiber-rubber Composites with Reclaimed Rubber

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BIORESOURCES 2018年第2期13卷 3300-3314页

作者： Shao, Dongwei Xu, Min Cai, Liping Shi, Sheldon Q. Northeast Forestry Univ Key Lab Biobased Mat Sci & Technol Minist Educ Harbin 150040 Heilongjiang Peoples R China Jiamusi Univ Coll Mech Engn Jiamusi Peoples R China Univ North Texas Mech & Energy Engn Dept Denton TX 76201 USA

This research investigated the use of reclaimed rubber (RR) from waste tires to partially replace the rubber compound (RC) when making wood fiber-rubber composites (WRCs). Ninety panels of WRC containing RR were manufactured with RR contents of 0% to 40%, mixing times of 6 min to 14 min, and vulcanizing temperatures of 150 degrees C to 170 degrees C. There were three steps, which were the fiber-rubber mixing, tabletting, and vulcanization molding processes. Four regression equations for the tensile strength, elongation at break, hardness, and rebound resilience as functions of the RR content, mixing time, and vulcanizing temperature were derived, and a nonlinear programming model was developed to obtain the optimum panel properties. It was found that when the RR content was within 20%, the wood fibers were well encapsulated and embedded in the RC/RR blends, and the processability of the WRCs were improved by adding RR. The incorporation of RR into the WRCs increased the average tensile strength and hardness by 33.9% and 2.3%, respectively, while the swelling ratio in toluene and 24-h water absorption were reduced by 13% and 42%, respectively.

关键词： Wood rubber composites (WRCs) Reclaimed rubber (RR) Panel properties nonlinear programming model

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Non-linear programming method for multi-criteria decision making problems under interval neutrosophic set environment

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APPLIED INTELLIGENCE 2018年第8期48卷 2199-2213页

作者： Garg, Harish Nancy Thapar Univ Patiala Sch Math Patiala 147004 Punjab India

Interval neutrosophic sets ( INSs) capturing the uncertainties by characterizing into the intervals of the truth, the indeterminacy, and the falsity membership degrees, is a more flexible way to explore the decision- making applications. In this paper, we develop a nonlinear programming ( NP) model based on the technique for order preference by similarity to ideal solution ( TOPSIS), to solve decision- making problems in which criterion values and their importance are given in the form of interval neutrosophic numbers ( INNs). Based on the concept of closeness coefficient, we firstly construct a pair of the nonlinear fractional programming model and then transform it into the linear programming model. Furthermore, to determine the ranking of considered alternatives, likelihood- based comparison relations are constructed. Finally, an illustrative example demonstrates the applicability of the proposed method for dealing with decision making problems with incomplete knowledge.

关键词： Neutrosophic set Interval neutrosophic set nonlinear programming model Multi criteria decision-making TOPSIS

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Integral Function to Optimize Mass Exchange Network Synthesis model

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JOURNAL OF CHEMICAL ENGINEERING OF JAPAN 2020年第6期53卷 254-266页

作者： Hou, Chuang Xu, Wenxing Luo, Mingsheng Beijing Inst Petrochem Technol Coll Chem Engn 19 North Qingyuan Rd Beijing 102617 Peoples R China Beijing Univ Chem Technol Coll Chem Engn North Third Ring Rd 15 Beijing 100029 Peoples R China

A mass exchange network (MEN), which consists of one or more mass exchangers, is a useful tool to realize pollution prevention in process industries. When a staged column is employed as a mass exchanger to synthesize a MEN, the number of trays must be rounded up to the next largest integer after obtaining an optimal design, which increases the capital cost. While designing a chemical process plant, when the capital cost increases, the operating cost should decrease. However, the operating cost was considered to be a fixed value in previous research even if the capital cost increased after rounding up the number of trays. Therefore, the total annual cost (TAC, including capital cost and operating cost) remained higher than the real optimal objective. To solve this problem, an integral function is added to the mathematical model to obtain the optimal MEN structure in this study. The application on two universal MEN synthesis mathematical models based on the Composition-Interval Diagram (CID) and stage-wise superstructure illustrate the practicability of the integral function. These modified models are applied to two examples of coke-oven gas sweetening and dephenolization of wastewater. The optimal results obtained in this study are found to be better in comparison to other works in the literature. This study demonstrates that the integral function can solve a series of MEN synthesis problems involving stage columns. Furthermore, a more accurate design scheme for MENS and a structure with lower TAC can be obtained by this function.

关键词： Mass Exchange Networks Process Optimization Integral Function nonlinear programming model Stage-wise Superstructure

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Optimization models to integrate production and transportation planning for biomass co-firing in coal-fired power plants

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IIE TRANSACTIONS 2016年第10期48卷 901-920页

作者： Eksioglu, Sandra Duni Karimi, Hadi Eksioglu, Burak Clemson Univ Dept Ind Engn Clemson SC USA

Co-firing biomass is a strategy that leads to reduced greenhouse gas emissions in coal-fired power plants. Incentives such as the Production Tax Credit (PTC) are designed to help power plants overcome the financial challenges faced during the implementation phase. Decision makers at power plants face two big challenges. The first challenge is identifying whether the benefits from incentives such as PTC can overcome the costs associated with co-firing. The second challenge is identifying the extent to which a plant should co-fire in order to maximize profits. We present a novel mathematical model that integrates production and transportation decisions at power plants. Such a model enables decision makers to evaluate the impacts of co-firing on the system performance and the cost of generating renewable electricity. The model presented is a nonlinear mixed integer program that captures the loss in process efficiencies due to using biomass, a product that has lower heating value as compared with coal;the additional investment costs necessary to support biomass co-firing as well as savings due to PTC. In order to solve efficiently real-life instances of this problem we present a Lagrangean relaxation model that provides upper bounds and two linear approximations that provide lower bounds for the problem in hand. We use numerical analysis to evaluate the quality of these bounds. We develop a case study using data from nine states located in the southeast region of the United States. Via numerical experiments we observe that (i) incentives such as PTC do facilitate renewable energy production;(ii) the PTC should not be "one size fits all";instead, tax credits could be a function of plant capacity or the amount of renewable electricity produced;(iii) there is a need for comprehensive tax credit schemes to encourage renewable electricity production and reduce GHG emissions.

关键词： Biomass co-firing biomass transportation integrated production transportation planning in supply chains Lagrangean relaxation linear approximation nonlinear programming model

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Protection coordination of directional overcurrent relays: new time current characteristic and objective function

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IET GENERATION TRANSMISSION & DISTRIBUTION 2018年第1期12卷 190-199页

作者： Yazdaninejadi, Amin Naderi, Mehdi S. Gharehpetian, Gevork B. Talavat, Vahid Urmia Univ Elect Engn Dept Orumiyeh Iran Amirkabir Univ IGSORC Tehran Iran Amirkabir Univ Elect Engn Dept Tehran Iran

Clearing power grid faults swiftly and selectively offers higher security, reliability and sustainability. Accomplishing this aim by deploying directional overcurrent relays (DOCRs) is one of the major challenges in meshed and multisource distribution networks. To overcome this challenge, the current study elaborates a new coordination strategy which concentrates on minimising overall operation time of relays. In this strategy, an auxiliary variable is added to classical operation time model of each DOCR. All the auxiliary variables are considered as coordination constraints which help to yield new and well-defined time current characteristics (TCCs). In other words, more flexibility is attained in adjusting relay's characteristic which helps to alleviate clearing time of faults. The obtained TCCs can be easily performed by numerical relays. In addition, a new objective function is defined to steer the relay settings towards optimal solutions conveniently. It was shown that the proposed approach not only reduces the operation time of relays, but also prevents miscoordinations. This approach demonstrates a non-linear programming model tackled by particle swarm optimisation algorithm. The effectiveness of the proposed approach is verified via 8-bus and IEEE 14-bus test systems and results are discussed in depth.

关键词： relay protection overcurrent protection power grids fault diagnosis power distribution protection nonlinear programming numerical analysis protection coordination directional overcurrent relays DOCR time current characteristic objective function power grid faults meshed distribution networks multisource distribution networks classical operation time model auxiliary variables coordination constraints TCC numerical relays operation time nonlinear programming model particle swarm optimisation algorithm 8-bus test systems IEEE 14-bus test systems

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A consensus reaching model for hesitant information with different preference structures

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KNOWLEDGE-BASED SYSTEMS 2017年 135卷 99-112页

作者： He, Yue Xu, Zeshui Sichuan Univ Sch Business Chengdu 610064 Peoples R China Nanjing Univ Informat Sci & Technol Sch Comp & Software Nanjing 210044 Jiangsu Peoples R China

Since the decision makers' experience, cognitions and knowledge background are quite different from each other, sometimes the preference information they provided may be various and different. In order to help the decision makers share information and make more reliable decisions, we design a consensus reaching model which consists of two parts: 1) selection process;2) conse nsus process. In this paper, we apply the hesitant fuzzy preference relations, the hesitant multiplicative preference relations and the hesitant preference orderings to express and integrate these complex preference information in a simple and convenient way. In the selection process, we propose a hybrid nonlinear programming model to process the information with different preference structures. This model overcomes the shortcomings of the traditional decision methods for hesitant information and obtains the decision results in a more accurate and reasonable way. In the consensus process, the consensus measure is put forward to judge whether the decision results are acceptable and identify which decision maker needs to modify his/her provided information. Then, an interaction mechanism is also proposed to help the decision makers exchange information and adjust the evaluation values. In the last, we apply the consensus reaching model to solve the hospital's trust evaluation problem and verify the stability of the model. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Consensus reaching model Hesitant fuzzy preference relation Hesitant multiplicative preference relation nonlinear programming model

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Group decision making model and approach based on interval preference orderings

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COMPUTERS & INDUSTRIAL ENGINEERING 2013年第3期64卷 797-803页

作者： Xu, Zeshui PLA Univ Sci & Technol Coll Sci Nanjing 210007 Jiangsu Peoples R China

In group decision making under uncertainty, interval preference orderings as a type of simple uncertain preference structure, can be easily and conveniently used to express the experts' evaluations over the considered alternatives. In this paper, we investigate group decision making problems with interval preference orderings on alternatives. We start by fusing all individual interval preference orderings given by the experts into the collective interval preference orderings through the uncertain additive weighted averaging operator. Then we establish a nonlinear programming model by minimizing the divergences between the individual uncertain preferences and the group's opinions, from which we derive an exact formula to determine the experts' relative importance weights. After that, we calculate the distances of the collective interval preference orderings to the positive and negative ideal solutions, respectively, based on which we use a TOPSIS based approach to rank and select the alternatives. All these results are also reduced to solve group decision making problems where the experts' evaluations over the alternatives are expressed in exact preference orderings. A numerical analysis of our model and approach is finally carried out using two illustrative examples. (C) 2013 Published by Elsevier Ltd.

关键词： Group decision making Interval preference orderings TOPSIS The simple additive weighted averaging operator nonlinear programming model

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Optimization models for operative planning in drinking water networks

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OPTIMIZATION AND ENGINEERING 2009年第1期10卷 43-73页

作者： Burgschweiger, Jens Gnaedig, Bernd Steinbach, Marc C. Leibniz Univ Hannover IfAM D-30167 Hannover Germany Berliner Wasserbetriebe Abt NA GW D-10864 Berlin Germany

The topic of this paper is minimum cost operative planning of pressurized water supply networks over a finite horizon and under reliable demand forecast. Since this is a very hard problem, it is desirable to employ sophisticated mathematical algorithms, which in turn calls for carefully designed models with suitable properties. The paper develops a nonlinear mixed integer model and a nonlinear programming model with favorable properties for gradient-based optimization methods, based on smooth component models for the network elements. In combination with further nonlinear programming techniques (Burgschweiger et al. in ZIB Report ZR-05-31, Zuse Institute Berlin, 2005), practically satisfactory near-optimum solutions even for large networks can be generated in acceptable time using standard optimization software on a PC workstation. Such an optimization system is in operation at Berliner Wasserbetriebe.

关键词： Drinking water supply Distribution network Minimum cost operative planning Continuous time model Mixed integer model nonlinear programming model

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Risk prioritization in failure mode and effects analysis under uncertainty

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EXPERT SYSTEMS WITH APPLICATIONS 2011年第1期38卷 206-214页

作者： Zhang, Zaifang Chu, Xuening Shanghai Jiao Tong Univ Sch Mech Engn Shanghai 200240 Peoples R China

Failure mode and effects analysis (FMEA) is a powerful tool for identifying and assessing potential failures. The tool has become increasingly important in new product development, manufacture or engineering applications. Generally, risk assessment in FMEA is carried out by using risk priority numbers (RPNs) which can be determined by evaluating three factors: occurrence (0), severity (S) and detection (D). Due to the vagueness and uncertainty existing in the evaluating process, crisp numbers representing RPNs in the traditional FMEA might be improper or insufficient in contrast to fuzzy numbers. Currently, the fuzzy methods and linear programming method have been proposed as an effective solution for the calculations of fuzzy RPNs. However, considering the fact that fuzzy RPNs are determined on a multidimensional scale spanning 0, S and D along with their interactions under a fuzzy environment, several gaps should be bridged in the evaluation, calculation, and ranking of fuzzy RPNs. First, decision makers tend to use multi-granularity linguistic term sets for expressing their assessments because of their different backgrounds and preferences. Second, numerical compensation may be existed among 0, S and D that can derive different RPNs in the engineering applications. Third, the complete ranking results for fuzzy RPNs may be easily changed by the effects of uncertain factors. In this study, a fuzzy-RPNs-based method integrating weighted least square method, the method of imprecision and partial ranking method is proposed to generate more accurate fuzzy RPNs and ensure to be robust against the uncertainty. A design example of new horizontal directional drilling machine is used for illustrating the application of the proposed approach. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Failure mode and effects analysis Fuzzy risk priority numbers Fuzzy weighted geometric mean nonlinear programming model The method of imprecision

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