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In this paper two procedures are developed for the identification of the parameters contained in an orthotropic elastic-plastic-hardening model for free standing foils, particularly of paper and paperboard. The experimental data considered are provided by cruciform tests and digital image correlation. A simplified version of the constitutive model proposed by Xia et al. (Int J Solids Struct 39:4053-4071, ) is adopted. The inverse analysis is comparatively performed by the following alternative computational methodologies: (a) mathematical programming by a trust-region algorithm; (b) proper orthogonal decomposition and artificial neural network. The second procedure rests on preparatory once-for-all computations and turns out to be applicable economically and routinely in industrial environments. [ABSTRACT FROM AUTHOR]

Abstract: To overcome declining markets and low-cost competition, Canadian pulp and paper (P&P) mills are considering the diversification of their product platform. Investing in bioenergy is emerging as a promising way to boost the sector. In this paper, we present a mathematical programming approach to evaluate the profitability of bioenergy investments in the case of a P&P mill, while assessing technical and associated economic risks. The mill, called the integrated forest biorefinery (IFBR), could produce a set of high-value bioproducts from biomass generated in the mill or supplied from outside. P&P activity generates residues, such as black liquor and pulp sludge, which could be used to produce bioenergy. P&P activity should then be well managed, by considering the possibility of temporarily stopping the production of P&P, while assuming the costs associated with the shutdowns. The objective is to develop a mathematically-based approach for investors and stakeholders, within the forest sector that aims to optimise the value creation network of the IFBR and to maximise the profitability of future investments in bioenergy, while optimising the existing P&P activity. [Copyright &y& Elsevier]

Using mathematical programming with activity-based costing (ABC) and based on the theory of constraints (TOC), this study proposed a green production model for the traditional paper industry to achieve the purpose of energy saving and carbon emission reduction. The mathematical programming model presented in this paper considers (1) revenue of main products and byproducts, (2) unit-level, batch-level, and product-level activity costs in ABC, (3) labor cost with overtime available, (4) machine cost with capacity expansion, (5) saved electric power and steam costs by using the coal as the main fuel in conjunction with Refuse Derived Fuel (RDF). This model also considers the constraint of the quantity of carbon equivalent of various gases that are allowed to be emitted from the mill paper-making process to conform to the environmental protection policy. A numerical example is used to demonstrate how to apply the model presented in this paper. In addition, sensitivity analysis on the key parameters of the model are used to provide further insights for this research. [ABSTRACT FROM AUTHOR]

This article presents several papers received for the November 1974 issue of the periodical "Management Science." Papers received include "Optimization of Traffic Signal Settings in Networks by Mixed-Integer Linear Programming," by N. Gartner, J.D.C. Little and H. Gabbay, "Intesections Cuts From Disjunctive Constraints," by E. Balas, and "Integer Programming," by Charles P. Bonini.

This note tries to answer issues raised in Bhardwaj and Kumar (J Optim Theory Appl 163(2): 685-696, 2014). The research summarizes that the results obtained in Khan et al. (J Optim Theory Appl 159: 536-546, 2013) are sound and correct and it fulfills all the necessary requirements of its scope and objectives. [ABSTRACT FROM AUTHOR]

Most laboratory assays take advantage of multi-step protocols to achieve high performance, but conventional paper-based tests (e.g., lateral flow tests) are generally limited to assays that can be carried out in a single fluidic step. We have developed two-dimensional paper networks (2DPNs) that use materials from lateral flow tests but reconfigure them to enable programming of multi-step reagent delivery sequences. The 2DPN uses multiple converging fluid inlets to control the arrival time of each fluid to a detection zone or reaction zone, and it requires a method to disconnect each fluid source in a corresponding timed sequence. Here, we present a method that allows programmed disconnection of fluid sources required for multi-step delivery. A 2DPN with legs of different lengths is inserted into a shared buffer well, and the dropping fluid surface disconnects each leg at in a programmable sequence. This approach could enable multi-step laboratory assays to be converted into simple point-of-care devices that have high performance yet remain easy to use. [ABSTRACT FROM AUTHOR]

This paper describes three-dimensional microfluidic paper-based analytical devices (3-D µPADs) that can be programmed (postfabrication) by the user to generate multiple patterns of flow through them. These devices are programmed by pressing single-use ‘on’ buttons, using a stylus or a ballpoint pen. Pressing a button closes a small space (gap) between two vertically aligned microfluidic channels, and allows fluids to wick from one channel to the other. These devices are simple to fabricate, and are made entirely out of paper and double-sided adhesive tape. Programmable devices expand the capabilities of µPADs and provide a simple method for controlling the movement of fluids in paper-based channels. They are the conceptual equivalent of field-programmable gate arrays (FPGAs) widely used in electronics. [ABSTRACT FROM AUTHOR]

The importance of linear programming, and especially mixed-integer linear programming, has increased over time as computers have gotten more capable, algorithms have improved and more software solutions have become available. This approach has been successfully applied for solving hard problems in operations research (like traveling salesman problem, routing problems and telecommunications network design problems). In the eighteenth paper, "Exact method for the two-machine flow-shop problem with time delays" Mkadem, Moukrim and Serairi propose an exact method for solving the two-machine flow-shop problem with time delays. [Extracted from the article]

Modular integrated construction (MiC) is an innovative construction method that is widely used in practice, but high transportation cost is an obstacle to its wider implementation. This paper is motivated by the real-world need for a scientific approach for MiC transport scheduling, and addresses the practical problem of how to achieve on-time door-to-door MiC delivery in an economical manner. An innovative integer programming model is formulated with the objective of minimising the total transportation costs, including trailer rental, fuel costs, and worker salaries. A case study based on Hong Kong data validates that the developed model can be efficiently solved for problems of practical size. The results also demonstrate that the derived MiC schedule plan can reduce transportation costs by 58.7% compared with a just-in-time (JIT) strategy, thus bringing great economic benefits to off-site construction practitioners. Useful managerial implications related to on-site MiC storage areas are derived through sensitivity analysis. Overall, this paper sets the ground for the application of mathematical programming methodology to the off-site construction field. Future research may be devoted to MiC transport scheduling under uncertainty. [ABSTRACT FROM AUTHOR]

• A generic mathematical model for the retrofit of water networks is developed. • The model is applicable to both direct reuse/recycling and regeneration schemes. • The model considers adding new pipes and modifying existing pipes. • Single- and multi-objective optimisation scenarios were presented with a case study. • Trade-offs among freshwater use, retrofit cost and modified pipes are explored. This work develops a generic mathematical model for process engineers and designers to retrofit existing water networks in process plants for water savings. The model is applicable to both direct reuse/recycling and regeneration schemes, with single- and multi-objective optimisation scenarios. The objectives of the model may include minimum water flowrates, minimum extent of retrofits and/or a reasonable payback period. A literature case study involving an existing water network in a pulp and paper mill is solved to elucidate the newly proposed model. The results of single-objective optimisation show maximum annual cost savings of $4,027,919 in the direct reuse/recycling scheme (with a 57.2% freshwater saving) and $4,420,975 in the regeneration scheme (with an 84.5% freshwater saving). For multi-objective optimisation, the use of the constraint method in the direct reuse/recycling scheme generates a range of Pareto optimal solutions for selection by the decision-maker. It was found that 88.1% of the freshwater saving can be achieved with 44.2% of the piping retrofit cost. Although the compromise solution obtained using fuzzy optimisation in the regeneration scheme achieves only 66.6% of the freshwater saving with 86% of the total retrofit cost, the number of new and modified connections is reduced by more than half. [ABSTRACT FROM AUTHOR]

Abstract: One of the desirable attributes of real-life examination timetabling solutions is the maximization of paper spread, which is a measure of the amount of study time that each student has between examinations. In this study, we face with a predefined examination schedule that must be modified in order to maximize paper spread in course of examination. We will show how the integer programming can be employed to achieve this aim. The model presents constraints for the quality of feasible examination timetables and all the requirements found in most academic institutions. The approach is tested on real-world exam timetabling problems. The computational experiments and results will be reported. [Copyright &y& Elsevier]

In a society where computers have become ubiquitous, it is necessary to develop a broader understanding of the nature of computing and programming, not just from a technical viewpoint but also from a historical and philosophical perspective. Computers and computer programs do not exist in a vacuum. Instead, they are a part of a rich socio-technological context that provides ways for understanding computers and reasoning about programs. This includes not only formal logic, mathematics, sciences, and technology but also cognitive sciences and sociology. The focus of this special issue is on questions that arise when we consider computing and programming in a wider context. In particular, the papers in this special issue explore the interplay between computing or programming and mathematics, formal logic, sciences, technology, and society. [ABSTRACT FROM AUTHOR]

Consider a nondifferentiable complex fractional programming $$ {\rm minimize} \, { {\rm Re} [ f(z, {\bar z}) + (z ^{H}Az) ^{1/2} ] \over {\rm Re} [ g(z, {\bar z}) - (z ^{H}Bz)^{1/2}} \qquad {\rm subject \, to} \, h(z, {\bar z}) \in S \subset C^{m}, \quad z \in C^{m}, \leqno (2) $$ where f, g : C2n → C and h : C2n → Cm are analytic functions, A, B ∈ Cn × n are positive semidefinite Hermitian matrices, S is a polyhedral cone in Cm. In this paper, we establish conditions for the existence of an optimal solution in (P) involving (ℒ, ρ, θ)-quasiconvex/-pseudoconvex analytic functions. Based on the sufficient optimality theorem, we construct a duality model and then establish weak/strong, and strict converse duality theorems. [ABSTRACT FROM AUTHOR]

Abstract. In the paper "On the nucleolus of the basic vehicle routing game", Mathematical Programming 72, 83-100 (1996), Gothe-Lundgren et al. develop a constraint generation method to compute the pre-nucleolus of a game. Their method assumes that constraints that are redundant in the representation of the core can be ignored in the computation of the prenucleolus. We provide an example that shows that for a game with an empty core such an assumption is, in general, not valid. Further, we show that a statement made by Gothe-Lundgren et al. about an intuitive interpretation of the pre-nucleolus is misleading. [ABSTRACT FROM AUTHOR]

The article announces that the paper "A smooth penalty approach and a nonlinear multigrid algorithm for elliptic MPECs," by Ian Kopacka and Michael Hintermüller in Volume 50 of the journal has received the "Best Paper Award" from the Computational Optimization and Applications.

The 2017 International Conference on Multiple Objective Programming and Goal Programming (MOPGP 2017) has been organized to disseminate recent theoretical and methodological developments, significant technical applications, case studies and survey results in the related area. Multiple Objective Programming (MOP), also known in literature as multi-objective optimization, vector optimization, multicriteria optimization, multiattribute optimization or Pareto optimization, is a subarea of Multiple Criteria Decision Making (MCDM) or Multiple Criteria Decision Analysis (MCDA) and it is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously. If we suppose that HT ht is ordered by the classical Pareto cone HT ht , then HT ht if HT ht . [Extracted from the article]

Motivated by recent investigations relating the sharpness of the Jensen inequality, this paper concerns with the sharpness of the converse of the Jensen inequality. For this reason, the Jensen inequality has become one of the most discussed developmental inequalities in the current literature on mathematical inequalities. In this Special Issue, we present new results related to classical inequalities, such as the Jensen inequality, Jensen-Steffensen inequality, Jessen inequality, Grüss inequality, Chebyshev inequality, etc. [Extracted from the article]

10.3390/math9172145 12 Oros G.I. Fuzzy Differential Subordinations Obtained Using a Hypergeometric Integral Operator. In accordance with Zadeh's definition, soft computing (SC) consists of computational techniques in computer science, machine learning, and some engineering disciplines to study, model, and analyze very complex realities, for which more traditional methods have been either unusable or inefficient. HC is bound by a computer science (CS) concept called NP-complete, which means that there is a direct connection between the size of a problem and the amount of resources needed to solve it called the "grand challenge problem". SC uses soft techniques, contrasting it with classical artificial intelligence hard computing (HC) techniques, and includes fuzzy logic, neural computing, evolutionary computation, machine learning, and probabilistic reasoning. [Extracted from the article]