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The steel industry is constantly facing problems and challenges that require optimisation to improve the production process. We present an algorithm to address a major challenge, the slitting problem, for a specific Spanish company. This problem arises when large steel coils need to be cut into smaller strips. Given the highly heterogeneous stock (coils come from previous operations), selecting the most suitable coils and defining the cutting patterns become very complicated due to operational and customer constraints. The company aims to reduce the leftovers and increase the service level (the difference between the weight requested by the customer and the weight supplied). The algorithm is currently in production and was validated using the company’s data and compared with an exact model. Results significantly improved the company’s operations, achieving a 50% reduction in leftovers and a much better service level in minutes, as opposed to the hours the company previously required. Although there are Mixed Integer Linear Optimization models that provide an optimal solution in small cases, they are not a viable alternative for the company because they require excessive computational time (even, in some cases, to obtain feasible solutions) and use overly expensive commercial solvers.

In global optimization problems, diversification approaches are often necessary to overcome the convergence toward local optima. One approach is the multi-start method, where a set of different starting configurations are taken into account to designate the best local minimum returned by the multiple optimization procedures as the (possible) global optimum. Therefore, parallelization is crucial for multi-start. In this work, we present a new multi-start approach for gradient-based optimization methods that exploits the reverse Automatic Differentiation to perform efficiently. In particular, for each step, this Automatic Differentiation-based method is able to compute the N gradients of N optimization procedures extremely quickly, exploiting the implicit parallelization guaranteed by the computational graph representation of the multi-start problem. The practical advantages of the proposed method are illustrated by analyzing the time complexity from a theoretical point of view and showing numerical examples where the speed-up is between ×40 and ×100, with respect to classic parallelization methods. Moreover, we show that our AD-based multi-start approach can be implemented by using tailored shallow Neural Networks, taking advantage of the built-in optimization procedures of the Deep Learning frameworks.

The current research paradigm for the frequency stability analysis of power systems is generally based on exploring the conditions of different new energy penetration rates. There is a lack of deep theoretical analysis on the frequency characteristics of power systems under the determined new energy penetration rate conditions. Under the determined new energy penetration rate, factors such as the start-up methods and frequency modulation depth of the power supply can also significantly affect the frequency characteristics. Based on the above, this study explores the problem of frequency characteristics analysis of power systems under determined new energy penetration rates considering different start-up methods and frequency modulation participation degrees. By calculating and analyzing the different system equivalent inertia formed by the heterogeneous power supply with different frequency modulation participation degrees and start-up methods/operation conditions, we discover the analytic solution and influence regularity of the frequency response under the condition of the determined new energy penetration rate. Finally, an arithmetic system was used to verify the correctness of the calculation method used in this study.

Purpose The purpose of this paper is to develop a generalized observer and controller for brushless direct current (BLDC) motor to make the system more robust for parameter variations, load torque and speed tracking. Design/methodology/approach A robust interconnection and damping assignment passivity-based control (IDA-PBC) technique for BLDC motor is introduced in this paper. The IDA-PBC is used to obtain the reference voltages for pulse width modulation (PWM) control. The immersion and invariance (I&I) observer is used to estimate the load torque and speed of the BLDC motor. At the time of starting, the motor rotates in arbitrary direction, and sometimes, because of the cogging action, it may take a huge current. Therefore, a new start-up method is proposed for the BLDC motor, which maintains the alignment of the rotor. Findings From the simulation and experimental results, it can be seen that the proposed controller and observer satisfactorily work for parameter variations, load torque and speed tracking. Originality/value The authenticity of the proposed technique is tested experimentally on two different BLDC motors using low-cost 32-bit STM32F407VG microcontroller. The response of the proposed technique is evaluated by changing motor parameters such as stator resistance, inductance, flux linkage constant and torque constant.

This paper deals with a multiobjective combinatorial optimization problem called Extended Knapsack Problem. By applying multi-start search and path relinking we rapidly guide the search toward the most balanced zone of the Pareto-optimal front. The Pareto relation is applied in order to designate a subset of the best generated solutions to be the current efficient set of solutions. The max-min criterion with the Hamming distance is used as a measure of dissimilarity in order to find diverse solutions to be combined. The performance of our approach is compared with several state-of-the-art MOEAs for a suite test problems taken from the literature.

The paper presents idea and practical implementation of a medium voltage synchronous drive with a voltage source inverter in the stator circuit and a microprocessor controlled unit for excitation supply. Construction of both devices was presented, and methods of their cooperation were described. Selected start-up methods of large power synchronous motors were presented. Exemplary realization was discussed. Measurement results of the direct full-voltage start-up and frequency start-up of a real 1.25 MW 6 kV fan drive system were compared and discussed.

Background, aim, and scope The start-up pattern of biofilm remediation system affects the biofilm characteristics and operating performances. The objective of this study was to evaluate the performances of the contaminated source water remediation systems with different start-up patterns in view of the pollutants removal performances and microbial community succession. Methods The operating performances of four lab-scale simulated river biofilm reactors were examined which employed different start-up methods (natural enrichment and artificial enhancement viadischarging sediment with influent velocity gradient increase) and different bio-fillers (Elastic filler and AquaMats® ecobase). At the same time, the microbial communities of the bioreactors in different phases were analyzed by polymerase chain reaction, denaturing gradient gel electrophoresis, and sequencing. Results and discussion The pollutants removal performances became stable in the four reactors after 2 months’ operation, with ammonia nitrogen and permanganate index (COD Mn ) removal efficiencies of 84.41–94.21% and 69.66–76.60%, respectively. The biomass of mature biofilm was higher in the bioreactors by artificial enhancement than that by natural enrichment. Microbial community analysis indicated that elastic filler could enrich mature biofilm faster than AquaMats®. The heterotrophic bacteria diversity of biofilm decreased by artificial enhancement, which favored the ammonia-oxidizing bacteria (AOB) developing on the bio-fillers. Furthermore, Nitrosomonas - and Nitrosospira -like AOB coexisted in the biofilm, and Pseudomonas sp., Sphaerotilus sp., Janthinobacterium sp., Corynebacterium aurimucosum were dominant in the oligotrophic niche. Conclusion Artificial enhancement via the combination of sediment discharging and influent velocity gradient increasing could enhance the biofilm formation and autotrophic AOB enrichment in oligotrophic niche.

Ecotoxicity assessments based on bacteria as model organisms are widely used for routine toxicity screening because it has the advantages of time-saving, high sensitivity, cost-effectiveness, and less ethical responsibility. Determination of ecotoxicity effect via bacterial growth can avoid the restriction of model bacteria selection and unique equipment requirements, but traditional viable cell count methods are relatively labor- and time-intensive. The Start Growth Time method (SGT) is a high-throughput and time-conserving method to determine the amount of viable bacterial cells. However, its usability and stability for ecotoxicity assessment are rarely studied. This study confirmed its applicability in terms of bacterial types (gram-positive and gram-negative), growth phases (middle exponential and early stationary phases), and simultaneous existence of dead cells (adjustment by flow cytometry). Our results verified that the stability of establishing SGT correlation is independent of the bacterial type and dead-cell portion. Moreover, we only observed the effect of growth phases on the slope value of established SGT correlation in Shewanella oneidensis , which suggests that preparing inoculum for the SGT method should be consistent in keeping its stability. Our results also elucidate that the SGT values and the live cell percentages meet the non-linear exponential correlation with high correlation coefficients from 0.97 to 0.99 for all the examined bacteria. The non-linear exponential correlation facilitates the application of the SGT method in the ecotoxicity assessment. Finally, applying the exponential SGT correlation to evaluate the ecotoxicity effect of copper ions on E. coli was experimentally validated. The SGT-based method would require about 6 to 7 h to finish the assessment and obtain an estimated EC 50 at 2.27 ± 0.04 mM. This study demonstrates that the exponential SGT correlation can be a high-throughput, time-conversing, and wide-applicable method for bacterial ecotoxicity assessment. Graphical abstract

En la actualidad, la agenda 2030 ha puesto las preocupaciones sociales y ambientales en el centro de la práctica empresarial. Esto ha impulsado a los nuevos emprendimientos a integrarlos a su modelo de negocio desde sus primeras etapas de desarrollo. Así, muchos de los comportamientos tradicionalmente asociados con las empresas sociales están siendo adoptados por las empresas ordinarias. Este proceso se menciona en la literatura como hibridación. En consecuencia, este enfoque híbrido sostenible adoptado por una cantidad cada vez mayor de nuevas empresas requiere el desarrollo de nuevas herramientas para diseñar, probar y escalar modelos de negocios sostenibles que aborden la integración de las preocupaciones sociales y ambientales en su modelo de negocios desde sus etapas iniciales de desarrollo. Sin embargo, hasta la fecha, no existe una herramienta disponible totalmente capaz de diseñar, probar y escalar modelos de negocios sostenibles.

This article studies the determinants of commercialization strategy for start-up innovators. We examine whether the returns on innovation are earned through product market competition or through cooperation with established firms (through licensing, alliances, or acquisition). Our hypotheses are that the relative returns to cooperation are increasing in (i) control over intellectual property rights, (ii) low transaction costs, and (iii) sunk costs associated with product market entry. Using a novel dataset of the commercialization strategies of start-up innovators, our results suggest that the procompetitive impact of start-up innovation-the gale of creative destruction-depends on imperfections in the market for ideas.