Search

Made available in DSpace on 2022-04-29T08:31:12Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-10-01 Organization and planning of reverse logistics networks make sustainable processes more efficient. Thus, an important sector for connecting the collection and waste paper recycling echelons is the intermediate center. In this study, a Mixed Integer Linear Programming model, which is multi-objective, multi-product, multi-level and multi-period, was developed to optimize the waste paper logistics processes of intermediate centers. The formulation includes the following echelons: collection, considering vehicle routing with different capacities; inventory of non-baling materials; baling sorted waste and inventory of bales; selling bales; disposal of non-recyclable waste. The aims of the model include: maximizing the collected waste; minimizing distances; maximizing both the production and sale of bales, and minimizing costs. According to research carried out in the literature, the developed model is a new proposal and to implement it, the Weighted Goal Programming and Revised Multi-Choice Goal Programming approaches were used to deal with multiple objectives and incorporate uncertainty into the quantity of waste available for collection. To analyze the proposed model, computational tests were executed with instances based on real data from a Brazilian company in the sector. For all performed tests, General Algebraic Modeling System 23.6.5 modeling language and CPLEX 12.2.0.2 solver were used for modeling and optimization. The results show that this study presents formulation and technological approaches that represent real situations and provide competitive solutions to the problem. Sáo Paulo State University “Júlio de Mesquita Filho” [Universidade Estadual Paulista Júlio de Mesquita Filho] School of Engineering of Guaratinguetá [Faculdade de Engenharia de Guaratinguetá] Production Department, Av. Ariberto Pereira da Cunha, 333, Portal das Colinas Agulhas Negras Military Academy [Academia Militar das Agulhas Negras] Rodovia Presidente Dutra, km 306, s/n Escola Preparatória de Cadetes do Exército Avenida Papa Pio XII 350 Jardim Chapadão Campinas - SP Brazil, Avenida Papa Pio XII, 350, Jardim Chapadão, Campinas - SP Sáo Paulo State University “Júlio de Mesquita Filho” [Universidade Estadual Paulista Júlio de Mesquita Filho] School of Engineering of Guaratinguetá [Faculdade de Engenharia de Guaratinguetá] Production Department, Av. Ariberto Pereira da Cunha, 333, Portal das Colinas

In this short communication the solution of a steady state model of a sextuple evaporator system used in a paper industry has been presented. With the help of the residual values of model equations (a set of 12 nonlinear algebraic equations) it has been shown that the presently obtained results are superior to the previously published results. The importance of the number of significant digits in calculation are also briefly discussed.

Availability analysis has been an important issue in the design field of any Industrial system as the system structure has become more complicated. Also, the system availability is affected by many factors such as design, manufacturing, installation, etc., and so it may be extremely difficult to model, analyze and predict the failure behavior of the system. The purpose of this paper is to develop a new approach for computing various performance measures, namely reliability, availability, MTBF (mean time between failures), ENOF (expected number of failures), failure rate and repair time, for any industrial system. In the proposed approach, the failure rates and repair times of all constituent components are obtained using genetic algorithms and then various performance measures are computed using fuzzy lambda–tau methodology. Washing system, the major part of paper industry is the subject of study. The interactions among the working components are modeled using Petri nets. Failure and repair rates are represented using triangular fuzzy numbers as they allow expert opinion, linguistic variables, operating conditions, uncertainty and imprecision in reliability information to be incorporated into system model. Based on calculated reliability parameters, a structured framework has been developed that may help the maintenance engineers to analyze and predict the system behavior.

We propose a new concept which is a generalization of fuzzy soft subset and fuzzy soft equal. Using such notions, we will be able to consider the distributive law of fuzzy soft sets. Using the distributive law of fuzzy soft sets, we point out that the distributive law of trapezoidal fuzzy soft sets as proposed by Xiao et al. (2012) is not true. The correction will further improve further extensions of the results of Xiao et al. (2012). We will also establish the generalized distributive law of trapezoidal fuzzy soft sets along with illustrative examples.

In this work we present a mathematical model describing the coupled heat and moisture transport in paper. The model is solved numerically and the numerical solution is used to study the interdependency of the moisture and temperature distribution in paper. The results show that variation with temperature of the saturated water vapor concentration and the sorption isotherm parameters are both important for inducing moisture desorption. It is also found that for steep relative humidity ramps moisture sorption generates temperature increments that slow down the sorption process itself. The model is also used to study the moisture gradients in a paper sheet inside a printer from Oce Technologies, which contains a warm print surface. The results predict changes in moisture content of only 0.2%, which suggests that no deformations are induced on the printed sheet.

Using advanced machine learning techniques as an alternative to conventional double-entry volume equations, a regression model of the inside-bark volume (dependent variable) for standing Eucalyptus globulus trunks (or main stems) has been built as a function of the following three independent variables: age, height and outside-bark diameter at breast height (DBH). The experimental observed data (age, height, outside-bark DBH and inside-bark volume) for 142 trees ( E. globulus ) were measured and a nonlinear model was built using a data-mining methodology based on support vector machines (SVM) and multilayer perceptron networks (MLP) for regression problems. Coefficients of determination and Furnival’s indices indicate the superiority of the SVM with a radial kernel over the allometric regression models and the MLP.

In this note, we point out an error in the recently published article [R.K. Mohanty, M.K. Jain, D. Dhall, A cubic spline approximation and application of TAGE iterative method for the solution of two-point boundary value problems with forcing function in integral form, Appl. Math. Model. 35 (2011) 3036–3047] and then correct it.

A multivariable, time invariant model for a Fourdrinier machine headbox is considered. Analysis procedures enabling safe, economical closed loop response regulation are outlined. An optimum, minimum control effort strategy is proposed. Simulated open and closed loop response records are computed. The effectiveness of the design procedure, which minimises the power consumption for regulation purposes improving reliability and reducing refit and maintenance costs thereby, is commented upon.

A wide range of mathematical models for multiple effect evaporators in process industry including paper industry are well reported in the literature but not so extensive work on the dynamic behavior of MEE system is available in the literature. In the present study dynamic behavior of multi-effect evaporator system of a paper industry is obtained by disturbing the feed flow rate, feed concentration, live steam temperature and feed temperature. For this purpose an unsteady-state model for the multi-effect evaporator system is developed. Each effect in the process is represented by a number of variables which are related by the energy and material balance equations for the feed, product and vapor flow. A generalized mathematical model which could be applied to any number of effects and all kinds of feeding arrangements like forward feed, backward feed, mixed feed and spilt feed in the MEE system with simple modifications was finally obtained. Finally model for mixed feed sextuple effect falling film evaporators system was solved using MATLAB. For the steady state and dynamic simulation the ‘fsolve’ and ‘ode45’ solvers in MATLAB source code is used respectively.

In the paper referred to in the title to this communication, Shahinpoor argued that increased density due to material consolidation of a bulk material in a vertical bin reduces the stresses the bulk material exerts on the bin wall below those that would be present if the material were unconsolidated. In this paper it is shown that increased density due to material consolidation actually increases rather than reduces these stresses. Shahinpoor's conclusions are incorrect because he misinterprets his analytical results.

Prediction models for specific energy consumption and throughput of palm nut–pulp separator were developed using mechanistic modeling technique. These models facilitate the easy production of different sizes of this machine in line with the budgets of the oil palm fruit processors. It also accounts for all the operational parameters of this machine as well as relevant properties of processed materials, digested palm fruit mash, palm nut and pulp. Experimental results indicated over 99% prediction accuracy of the models, while the prediction error of the specific energy consumption and throughput models are within the range of −0.014 to 0.076% and −0.005 to 0.003% respectively.

Automation is being accepted for control systems onboard ships in view of the shortage of skilled manpower in marine sector. Control theory has long been applied to maneuvering problems and at present this trend is continuing at an increased rate. This is for speed control, course control and path keeping. Heading control and course keeping are very important for surface ships while they enter shallow water regions. A typical situation is the entry of a large commercial ship into the harbour basin. The ship faces a sudden change of forces and moments around it due to the change in the hydrodynamics. The Master of the ship regulates the speed while entering the basin. Forces and moments, due to the hydrodynamic flow around the moving hull, are balanced by the rudder behind it. The feed back from the heading angle is taken and the gain in the control system prompts the steering gear to turn the rudder. The conventional control algorithm based on PID is attempted in the first part of the paper and case studies are shown for a Mariner class ship whose hydrodynamic derivatives are known. Displacement, velocities and accelerations are determined for short duration from the simulation of a voyage in calm water. The proposed system can be implemented into autopilot systems. The codes developed in MATLAB can accommodate wind and wave forces as well. The simulation is of a general type and can be used for other vessels with a change in the constants of P (Proportional), I (Integral) and D (Derivative) which can be arrived at by trial and error. The design of the control system depends on the choice of the three control constants Kp, Ki and Kd. These will change as per sea state and extra loads. The control of motions in shallow water and deep water cases are discussed in the paper. In the next part of the paper, fuzzy logic control is discussed. Fuzzy logic is applied to control the heading and bring the path of the vessel to the desired level. The models discussed are versatile because of the provision for add-on facility for wind, wave or any other environmental loads. The rudder turning rate is taken as that for commercial ships. In the near future, a combined control system for ship maneuvering can be possible by considering both the PID and Fuzzy based algorithm. The two algorithms with suitable modifications are useful for non-linear cases. It is also tried to compare the two methods and an attempt is made to find out which is better and acceptable. � 2008 Elsevier Inc. All rights reserved.

A five-tank anaerobic-anoxic/oxic (A2/O) activated sludge process was investigated as innovative configuration in the activated sludge process technologies which has advantage of save energy power, cost and enhance nitrogen and phosphorus removal whereas it does not need equipment for sludge and mixed liquor recycle and also it required small land for construction. The five-tank process achieved 89.1% ± 1.37%, 87.78% ± 1.15%, 73.62% ± 2.13%, and 83.78% ± 0.92% of chemical oxygen demand, NH 4 + –N, TN, and total phosphorus (TP) removal efficiencies, respectively, during a 16-month operation with the effluent meeting Chinese sewage discharge standard GB18918-Grade A. A computer program was built based on activated sludge model No. 2d for simulating the performance of each compartment in five-tank process. The difficulty of simulation is coming from the system operation condition where it is operated under unsteadily state condition in all its compartments .The results showed that the growth rate constant of autotrophic organisms was 2.4 day−1 and yield coefficient was 0.14. According to simulation results, heterotrophic organism; phosphate accumulating organism, and autotrophic organism are decreased in the anaerobic compartments because of the lysis reaction. Then these organisms are increased in the aerobic compartments due to aerobic growth. The heterotrophic organism; phosphate accumulating organism; and autotrophic organism are increased in quantities by about 56.6%, 36.12% and 74.31% in compartment one due to change the operation condition from anaerobic to aerobic and decreased in quantities by about 20.21%, 44.18%, and 0.142% in the compartment three due to change from aerobic to anoxic. The total nitrifying species to total active biomass was fluctuated between 1–11.89% in the process reactor.

This paper summarises the development, implementation and typical results from a new full-scale three-dimensional numerical model of the multiphase chemically reacting flow in a continuous digester. The model is based on continuity and momentum equations for wood chips and free liquid. A new sub-model describing the tangential stresses for the solid phase has been developed and incorporated into the digester model. The solution procedure that takes into account the high inter-phase friction terms and the high values of the solid pressure has been introduced. In order to illustrate the model’s performance, simulations have been carried on for the industrial digester. The results are in quantitative agreement with available field measurements and in qualitative agreement with operating personnel observations. The model utilises curvilinear body fitted coordinates and can be used to simulate the operation of various pulp digesters or any other chemical reactors working in a similar regime.

In order to investigate the influence of mixed liquor inorganic suspended solids (MLISS) on membrane flux at different ratio of sludge retention time (SRT) to hydraulic retention time (HRT) in a submerged membrane bioreactor (SMBR), a pilot scale test was conducted for 452 days using traditional Chinese medicine (TCM) wastewater as influent. SRT/HRT was controlled at 150, 480 and 750, respectively. The experimental results showed that the average values of MLISS were 1271.9, 1664.5 and 6898.8 mg/L at different SRT/HRT, respectively; MLISS were accumulated from 265.5 g/h to 4912.93 g/h, which indicated that SMBR could not steadily operate for a long period without sludge withdrawal. Sludge oxygen utilized rate (SOUR) decreased from 5.115 to 1.292 mgO 2 /(gVSS h) and volume oxygen utilized rate (VOUR) increased from 10.84 to 18.13 mgO 2 /(L h). Model of membrane flux and MLISS were developed under different temperature and operational pressure by regressions, which were then satisfactorily employed to predict the trend of membrane flux during the experiment.

A simple anaerobic digestion (AD) model was formulated with emphasis on understanding the microbial activity during AD. The model was formulated according to two main rules that regulate the microbial growth. The first rule was maintaining the elemental continuity of macronutrients C, H, N, O, P, and S. The second rule satisfied the thermodynamics of the main AD catabolic reactions: acidogenesis and both acetotrophic and hydrogenotrophic methanogenesis. Accordingly, the stoichiometric parameters were evaluated as functions of the bacterial yield. The model also considered the enzymatic hydrolysis of solid waste. For a known solid waste composition, experimental data was utilized to estimate microbial initial concentrations, yields and kinetics, i.e., to achieve better understanding of the main AD microbial activity. The model was applied to three sets of batch experiments focusing on anaerobic dairy manure degradation. The model predicted the degradation dynamics, estimated the bacterial concentration in different inoculums, and evaluated the effect of inoculum ratios in speeding up the degradation. Elemental continuity based formulation of the model evaluated additional components that are necessary for future studies of macronutrients recovery, limitation/toxic effects, and chemical equilibrium.

The Activated Sludge Model No. 2d (ASM2d) was employed and modified to predict the effluent qualities of the modified enhanced biological phosphate removal (EBPR) system – TNCU. The TNCU process was composed of anaerobic/anoxic/oxide (A2O) process and rotating biological contactors (RBC) in each reactor. There were three modifications for the model in this study: (1) the biosorption effect of the soluble COD, (2) the ammonification of the organic nitrogen in influent wastewater, and (3) the growth of the heterotrophic organisms in the anaerobic tank. The influent wastewater qualities were fixed, the ratios of return sludge and SRT were 0.5 and 11 days, and the model plant was operated at three different mixed liquid recycling ratios (MLRR, 0.5, 1.25, 2). When a steady state was reached, the comparisons between the measured values and the model predicted values in each test were made. It shows a good consistency between them. According to the consistent results, the biosorption effect of the soluble COD and the ammonification of the organic nitrogen in influent wastewater were the important effects in activated sludge system. Additionally, the heterotrophic organisms might grow in the anaerobic tank. The heterotrophic organisms, phosphorus accumulating organisms and autotrophic organisms would decrease in the anaerobic tanks because the lysis reactions were the major reactions in the anaerobic tanks. They would increase in the aerobic tanks. Furthermore, it was indirectly proved that the denitrifying PAOs existed in the EBPR system.

This study sets out to examine whether the demand for softwood lumber in the United States is responsive to various market factors including the price of softwood lumber, the price of other building materials, and the level of economic activity (e.g., housing starts). Concern in the analysis is focused on overcoming some of the methodological shortcomings found in previous studies of this issue. The results are conclusive. The quantity of softwood lumber demanded does respond to the various economic factors considered. Moreover, when the structural stability of the estimated relationships is investigated, the results suggest that the demand for softwood lumber regionally in the United States has remained unaltered over the sample period (1950–1985).

This short paper extends the results of the paper on ‘Fitting continuous-time and discrete-time models using discrete-time data and their application’ (Zhu J., Shieh, L. S. and Yates, R. E.: Appl. Math. Modelling 1985, 9, 93) to systems with multiple poles.

A rigorous analytical justification is developed for a simplification that is widely used in one-dimensional simulations of steady and unsteady flows in pipes, namely treating the flow as a 'plug flow' in which cross-sectional variations in axial velocity are neglected except for consequential shear forces on pipe walls. The proof is obtained without assuming that the flow is nearly incompressible flow and, indeed, it is found that the plug flow approximation remains good even for compressible flows at moderate, subsonic speeds. In more general analyses, explicit allowance is sometimes made for the influence of (i) the Boussinesq coefficient β and (ii) its axial rate of change ∂β/∂x. Typically, such analyses discard the terms in ∂β/∂x in the basic equations and proceed using β alone. This is done on the grounds that no method of evaluating ∂β/∂x is available. It is shown in this paper that discarding ∂β/∂x is not only unnecessary, but that it actually leads to less accurate outcomes than simply assuming plug flow. The process used to derive the analytical justification has a spin-off benefit of shedding light on alternative methods of integrating source terms over the pipe cross-section. Although the primary purpose of the paper is to demonstrate that the use of plug flow approximations can be justified rigorously for most flows, brief attention is also paid to cases where it has potential to mislead.

Funding Information: The first author thanks the Natural Sciences and Engineering Research Council of Canada (NSERC) for their financial support. The authors thank the anonymous reviewers for their positive feedback and valuable comments. Publisher Copyright: © 2022 The economic order/production quantity (EOQ/EPQ) model is the most celebrated and the first scientific treatment of inventory management. It has been a fundamental topic covered in all production and operations management textbooks and the edifice on which complex inventory and logistics models have been built. It has been extended in many ways to make it more representative of real situations and settings. One of these extensions, which is the focus of the paper, is learning in production, where inventory builds in a convex rather than a linear form. Starting from the seminal work of Keachie & Fontana (Management Science, 13(2), B-102, 1966), this paper reviews the mathematics of those papers that stemmed from that work in an attempt to provide almost a comprehensive but rather concise presentation of more than 50 years of mathematical modeling. It also provides numerical examples to illustrate the expected behavior when learning occurs in activities other than production (setups and quality). It concludes with some insights and suggestions for future research directions for those who continue to be interested in the topic.

This paper develops a model for a cold chain operated among a single product manufacturer and multiple retailers to minimize the total cost of the chain. A distinguishing feature of the cold chain is that the quality of the product degrades with time. The storage temperature and time influence the degradation rate. In this context, quality can be measured using multiple distinct indices. A global stability index is used to quantify the overall quality. The non-Arrhenius model is exclusively applied to measure the quality degradation during the transportation and at a retailer's storage as the product moves in the cold chain. Optimal replenishment times for the manufacturer and retailers are decision variables and the cold chain's total cost includes the cooling cost, carbon emission cost, and loss of value in addition to the traditional supply chain costs. It is found that for a given manufacturer's replenishment time, the total cost is convex on each retailer's replenishment time. Hence, an algorithm is developed based on this property to find the optimal replenishment times for the manufacturer and retailers. This paper also investigates how specific cold chain parameters influence optimal decisions and the total cost. The analyses show that the resulting costs will be significantly higher if quality degradation is ignored in a cold chain.

The traditional models for the analysis of the accelerated test data cannot physically explains how the environment affects lifetime and its uncertainty. To solve this problem, this paper utilizes the theory of open quantum system, the theory about random behaviour of microparticles under the external environment, to describe the effects of stresses on lifetime uncertainty. The interaction between the system and environments motivates us to describe the accelerated test data from a quantum perspective. A quantum master equation is used as the reliability dynamics, which can be separated into a conservation term and a decay term. Then, the acceleration model is further incorporated into the decay term of the dynamic and forms a semi-quantum model. A practical procedure is proposed to obtain the initial guesses of parameters and do a graphic check on the assumption. Applications on two sets of real accelerated life test data show the proposed model outperforms the existing ones and hence verify its validity. This paper makes the first attempt to quantify the uncertainty under different environments from a quantum perspective and shows that it is feasible to utilize quantum theory to make a further exploration.

International audience; In this paper we study a single machine scheduling problem with the objective of minimizing the sum of completion times. Each of the given jobs is either short or long. However the processing times are initially hidden to the algorithm, but can be tested. This is done by executing a processing time oracle, which reveals the processing time of a given job. Each test occupies a time unit in the schedule, therefore the algorithm must decide for which jobs it will call the processing time oracle. The objective value of the resulting schedule is compared with the objective value of an optimal schedule, which is computed using full information. The resulting competitive ratio measures the price of hidden processing times, and the goal is to design an algorithm with minimal competitive ratio. Two models are studied in this paper. In the non-adaptive model, the algorithm needs to decide beforehand which jobs to test, and which jobs to execute untested. However in the adaptive model, the algorithm can make these decisions adaptively depending on the outcomes of the job tests. In both models we provide optimal polynomial time algorithms following a two-phase strategy, which consist of a first phase where jobs are tested, and a second phase where jobs are executed obliviously. Experiments give strong evidence that optimal algorithms have this structure. Proving this property is left as an open problem

The paper presents a method for determining maintenance and spare provisioning costs, for systems containing a non exponential component. The input data of the model are R ( t ) - the reliability function with time of the component, T the duration of the life cycle, cost of a repair, cost of a spare part and the turnaround time. The model is applicable for any form of R ( t ) : Weibull, Normal, expressed by an explicit or implicit set of equations and even in the form of discrete frequency table. The calculations can be performed by a simple Excel worksheet and do not require expensive tools (e.g. a flexible Monte Carlo package): The algorithm requires a few iterations of the dot product of two matrices. The entries of the matrices are calculated from the input values and the results of previous iterations, at M equidistant time points along the life cycle. M determines the accuracy of the calculations. The paper indicates sufficient conditions for M , which ensure a desired accuracy. Numerical examples performed on an Excel worksheet are presented. Since the model is applicable for any R ( t ) , it was applied, for verification purposes for R ( t ) = e − λ t , which has well known accurate results. The comparison confirmed the accuracy of the approximations.

In order to simulate the elastic wave propagation in unbounded solids, this paper introduces a non-local method to construct absorbing boundary conditions in the bond-based peridynamic theory. To construct non-local absorbing boundary conditions in the form of absorbing layers with increasing damping, we first re-derived the particle motion equilibrium equation of the bond-based peridynamic theory, based on the principle of virtual work and Lagrange's equation on the premise of considering material damping. We also give the expression for the inter-particle damping force density which satisfies the balance laws of linear momentum and angular momentum. This paper also provides a process and algorithm for realizing the non-local absorbing boundary conditions in the bond-based peridynamic theory, and adopts the Fortran language for computer program compilation. Finally, we simulate the elastic wave propagation in semi-unbounded and unbounded solids as numerical examples. The results show that such non-local absorbing boundary conditions can stably absorb and attenuate incident elastic waves. Since it is derived in the time domain, this method does not require frequency-domain operations, such as Fourier and Laplace transformations, nor does it require wave field splitting.

This paper presents a novel in-silico framework for the simultaneous optimal control and design of complex magnetic responsive polymer composite materials. State-of-the-art optimisation techniques are used in conjunction with the latest developments in the numerical solution of hard-magnetic soft materials undergoing large (potentially extreme) deformations, in order to address the challenging task of designing shape-morphing two-dimensional composite magnetic sheets. This paper introduces the following key novelties: (i) an optimisation-driven method for the simultaneous optimal control and design of the externally applied magnetic flux density as well as the remnant magnetisation of hard particles within the elastomer matrix, (ii) the well-posedness character of the optimisation problem is established by proving existence of solutions for both the underlying state equation and the control problem itself, (iii) a gradient-based optimisation algorithm is proposed for the numerical approximation of the problem, where explicit expressions of the continuous gradients are obtained by using the formal Lagrangian method. Furthermore, a series of numerical examples are presented in order to demonstrate the capability of the proposal as an alternative to intuition or experimentally-based approaches, representing an optimisation-driven method that facilitates the design of smart materials yielding complex magnetically induced shape morphing configurations.

A novel least squares twin support vector regression method is proposed based on the robust L1-norm distance to alleviate the negative effect of traffic data with outliers. Although there is some known work for the short-term traffic flow prediction problems, their efficacy depends heavily on the collected traffic data, which are often affected by various external factors (e.g. weather, traffic jam or accident), leading to errors and missing data. This makes it difficult to pick an effective method that accurately predicts the traffic state. As a contribution of this paper, an iterative algorithm is designed to solve the non-smooth L1-norm terms of our method; its convergence also proved. Further, a comprehensive traffic flow indicator system based on speed, traffic flow, occupancy and ample degree is utilized in this paper. We also extend the proposed method to a nonlinear version by hybridizing the polynomial kernel and radial basis function kernel, where the weight coefficient of hybrid kernel is determined by the change tendency of traffic data. To promote the prediction performance, the parameters of our nonlinear method are optimized by adaptive fruit fly optimization algorithm. Extensive experiments on real traffic data are performed to evaluate our model. The results indicate that the newly constructed model yields better prediction performance and robustness than other models in various experimental settings.

To solve the design problems of engineering structures with multiple conflicting performance indices under uncertainties, a non-probabilistic optimization model which takes into consideration the correlation of uncertainties was proposed in this paper. The multidimensional parallelepiped model was utilized to describe the uncertainties and deal with their correlation. Further, a novel concept of feasible discriminant of interval constraints was proposed to identify the feasible solutions, and a competitive strategy for design vectors was proposed to achieve equilibrium design of structures. To improve the efficiency of optimization and promote its applications in engineering, a direct solution framework was constructed in this paper. This framework was based on response surface model and integrated the interval analysis with the genetic algorithm. The effectiveness and superiority of the proposed approach were illustrated by two numerical examples. Finally, the proposed method was applied to structural design of the upper and lower beams of forming machine, and the design of lightweight and equilibrium were achieved. This structural design example demonstrated the applicability and effectiveness of the proposed method in engineering.

Funding Information: The first author thanks the Finnish Work Environment Fund (No. 200224) for supporting this research. The second author sincerely thanks Prof. Charles D. Bailey of James Madison University for making his data available. Without it, this study would not have been possible. He also conveys his thanks to the Social Sciences and Humanities Research Council (SSHRC) of the Canada-Insight Grant Program (No. 435-2020-0628) for supporting this research. Funding Information: The first author thanks the Finnish Work Environment Fund (No. 200224 ) for supporting this research. The second author sincerely thanks Prof. Charles D. Bailey of James Madison University for making his data available. Without it, this study would not have been possible. He also conveys his thanks to the Social Sciences and Humanities Research Council (SSHRC) of the Canada-Insight Grant Program (No. 435-2020-0628 ) for supporting this research. Publisher Copyright: © 2021 Production and operations management (POM) uses learning curve (LC) models to determine the length of training sessions for new workers and predicting future task performance. Empirically validated LC parameters provide managers with quantitative information on the effects of the presumed factors behind the learning process. Previous studies considered LC to compose of cognitive and motor curves. Another widely acknowledged but only recently parameterized phenomenon in the POM field is interference, which assumes some loss of information or experience could occur over a learning session. This paper takes a logical step in this line of research by developing an interference-adjusted power LC model, a composite of cognitive and motor elements. This paper accounts for the decay of cognitive and motor memory traces from repetitions to measure the residual (interference-adjusted) experience and capture these phenomena. Three variants of the model are developed that assume power and exponential decay functions and an approximate version of the exponential one. Assembly data representing various forms of an individual learning profile have been used to test the fits of the developed models. In addition to those models, four potential models from the literature were selected for comparison purposes. The results show that the approximate model fits very well exponential learning profile. The findings highlight the confluence of the three phenomena in learning, component (cognitive/motor) learning, interference, and plateauing. (c) 2021 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

Introduced in this paper is the complete nonlinear model of the micropolar theory (MPT) for shell-type materials. Considering the three-dimensional kinematic model in a convected curvilinear coordinate system, the Lagrangian description of micromorphic theory (MMT) is formulated first. Due to certain assumptions, i.e. skew-symmetricity of micro-displacement and orthogonality of micro-deformation tensors, the highly nonlinear micropolar continuum theory is obtained. Unlike the conventional knowledge in the literature, it is found that not only MPT is not a simple version of MMT but also the present micropolar formulation can be reduced to the corresponding micromorphic shell elasticity. Also, unlike the Kafadar-Eringen's nonlinear micropolar model which only predicts the large micro-deformations, the developed micropolar theory is able to investigate the physical behavior in case of large elastic macro-deformations, for the first time. The isogeometric analysis (IGA) solution method with standard base functions is used to prevent the locking issues arising in the low-order finite element analysis (FEA) of thin shells. Accordingly, the proposed IGA micropolar shell model possesses 10-DOFs (degrees of freedom) standing for 7 macro-displacements and 3 micro-rotations. Size / inhomogeneity effects of small-scale / micropolar materials are investigated in the benchmark problems of geometrically nonlinear shells. As a result, it is revealed that the paper contributes to literature by developing the nonlinear micropolar shell theory which is able of capturing large macro- and micro-deformations.

The integrated lot-sizing and cutting-stock problem has become a trend in the last decades for its applicability and advantage. Consequently, different approaches and formulations have been developed. One of them, which is widespread and related to the production and cutting process of paper, is the research subject of this paper. Fundamental considerations about the literature model are discussed and an alternative formulation is proposed, which consists of a simplified version that can provide better solutions. The upgrade modifications are proved analytically and an instance is analyzed to exemplify the discussed improvement. Moreover, computational tests are performed to compare both formulations. The novelty of the proposed formulation is the possibility of finding better solutions through the reduction of a constraint set, which guarantees the flexibility given by item and object inventories in meeting demand and it also enables a reduction in the total amount of produced paper. The proposed formulation has a significant impact on future research since the addressed model is the target of many scientific researches and practical applications.