Parallel Machine Scheduling (PMS) is a well-known problem in modern manufacturing. It is an optimization problem aiming to schedule n jobs using m machines while fulfilling certain practical requirements, such as total tardiness. Traditional approaches, e.g., mix integer programming and Genetic Algorithm (GA), usually fail, particularly in large-size PMS problems, due to computational time and/or memory burden and the large searching space required, respectively. This work aims to overcome such challenges by proposing a heuristic-based GA (DAS/GA). Specifically, a large-scale PMS problem with n independent jobs and m identical machines with a single server is studied. Individual heuristic algorithms (DAS) and GA are used as benchmarks to verify the performance of the proposed combined DAS/GA on 18 benchmark problems established to cover small, medium, and large PMS problems concerning standard performance metrics from the literature and a new metric proposed in this work (standardized... [more]

Rice bran is a by-product of the rice milling process. It contains a high concentration of protein. Rice brans are frequently utilized as feed cattle, fertilizer, and fuel. However, their application as human nutrition supplements is uncommon, and the necessary process for this purpose is yet to be established, including the drying process. This study aims to evaluate the effect of the spray-drying parameters, the inlet temperature, inlet flowrate, and inlet air flowrate, on rice bran protein (RBP) powder and optimize it using response surface methodology (RSM). A thermal water-based extraction method was utilized prior to the drying process. The correlation between the spray-drying parameters, i.e., the inlet temperature (120 to 210 °C), feed flowrate (5 to 55%), and air flowrate (246 to 670 L/h), and the RBP yield were investigated. The quality of the RBP powder was evaluated based on acid amino profiling in the mixture through de novo peptide sequencing. The optimized operating cond... [more]

It is becoming increasingly difficult to properly control the power consumption of widely dispersed data centers. Energy consumption is high because of the need to run these data centers (DCs) that handle incoming user requests. The rising cost of electricity at the data center is a contemporary problem for cloud service providers (CSPs). Recent studies show that geo-distributed data centers may share the load and save money using variable power prices and pricing derivatives in the wholesale electricity market. In this study, we evaluate the problem of reducing energy expenditures in geographically dispersed data centers while accounting for variable system dynamics, power price fluctuations, and renewable energy sources. We present a renewable energy-based load balancing employing an option pricing (RLB-Option) online algorithm based on a greedy approach for interactive task allocation to reduce energy costs. The basic idea of RLB-Option is to process incoming user requests using ava... [more]

The COVID-19 pandemic broke out and the global logistics industry suffered severe losses; therefore, the Fuzzy FMEA-AHP (Fuzzy Failure Mode and Effects Analysis-Analytic Hierarchy Process) method is proposed to analyze the failure reasons of the logistics system in the COVID-19 pandemic. In this article, we have made an optimization on the basis of the FMEA method: the fuzzy is integrated into the FMEA algorithm, referred to as F-RPWN (fuzzy risk priority-weighted number). Meanwhile, the AHP is used to determine the weights of risk indicators. In this article, we consider new logistics failures, such as the failure modes and failure reasons of the logistics system under the COVID-19 pandemic. There are 12 failures that have been determined, and relevant preventive and corrective measures have been recommended to cut off the path of failure propagation and reduce the impact of failures. In addition, the proposed method can help logistics firms, their supply chain partners, and customers... [more]

In bakery production, to perform a processing task there might be multiple alternative machines that have the same functionalities. Finding an efficient production schedule is challenging due to the significant nondeterministic polynomial time (NP)-hardness of the problem when the number of products, processing tasks, and alternative machines are higher. In addition, many tasks are performed manually as small and medium-size bakeries are not fully automated. Therefore, along with machines, the integration of employees in production planning is essential. This paper presents a hybrid no-wait flowshop scheduling model (NWFSSM) comprising the constraints of common practice in bakeries. The schedule of an existing production line is simulated to examine the model and is optimized by performing particle swarm optimization (PSO), modified particle swarm optimization (MPSO), simulated annealing (SA), and Nawaz-Enscore-Ham (NEH) algorithms. The computational results reveal that the performance... [more]

Copper losses during the Peirce-Smith converter (PSC) operation is of great concern in the copper smelting process. Two primary objectives of the PSC are to produce blister copper with a shorter batch time and to keep the copper losses at a minimum level. Due to the nature of the process, those two objectives are contradictory to each other. Moreover, actions inside the PSC are subject to several operational constraints that make it difficult to develop a scheduling framework for its optimal operation. In this work, a basic but efficient linear multi-period scheduling framework for the PSC is presented that finds the optimal timings of the PSC operations to keep the copper losses and the batch time at a minimum level. An industrial case study is used to illustrate the effectiveness of the proposed framework. This novel solution can be implemented in other smelting processes and used for the design of an inter-PSC scheduling framework.

In order to solve the problem of vigorous vibration of agricultural machinery frames, taking a vegetable precision seeder as an example, the concept of vibration reduction was proposed. The modal analysis of the frame was carried out, and the accuracy of the finite element model was verified by comparing the modal test of multipoint input and multipoint output (MIMO) and simulation results. Additionally, the main frequency of engine vibration was the main excitation source of frame resonance. According to the modal shapes, it was proposed to increase the fixed beam structure and to carry out simulation tests. The time-domain signal of the maximum deformation position in the first-order vibration mode was measured, and the vibration spectrum analysis maps before and after optimization were obtained by Fourier transform. A field experiment showed that the seeding quality of the whole machine was significantly improved after optimization. This study provides a reference for the analysis o... [more]

This study deals with the improvement in drying process performances and the quality of the final product for industrial equipment in the food industry. Designers need to optimize the design parameters of devices to create synergies between the greater energy efficiency of the process and high-quality dried products. Air impingement drying was carried out on apple cylinders at 323 K and with air velocities ranging between 30 and 60 m s−1. The studied drying process presents a particular setup of jets as they are multiple rectangular slot jets issued from triangular nozzles. The effect of four design jet parameters (slot width, nozzle-to-surface height, nozzle-to-nozzle spacing, and airflow) on the drying process performances and the quality of the final product was analyzed and optimized using response surface methodology (RSM). A minimal influence of design jet parameters on the process performances was shown, while an important impact was observed on the quality of dried apple. The s... [more]

Electrochemical impedance spectroscopy (EIS) is an important electrochemical technique that is used to detect changes and ongoing processes in a given material. The main challenge of EIS is interpreting the collected measurements, which can be performed in several ways. This article focuses on the electrical equivalent circuit (EEC) approach and uses grammatical evolution to automatically construct an EEC that produces an AC response that corresponds to one obtained by the measured electrochemical process(es). For fitting purposes, synthetic measurements and data from measurements in a realistic environment were used. In order to be able to faithfully fit realistic data from measurements, a new circuit element (ZARC) had to be implemented and integrated into the SPICE simulator, which was used for evaluating EECs. Not only is the presented approach able to automatically (i.e., with almost no user input) produce a more than satisfactory EEC for each of the datasets, but it also can also... [more]

In this paper, an approach for the tuning of a model-based non-linear predictive control (NMPC) is presented. The proposed control uses the pattern search optimization algorithm (PSM), which is applied to the pH non-linear control in the alkalinization process of sugar juice. First, the model identification is made using the Takagi Sugeno T-S fuzzy inference systems with multidimensional fuzzy sets; the next step is the controller parameters tuning. The PSM algorithm is used in both cases. The proposed approach allows the minimization of model uncertainty and decreases, in the response, the error in a steady state when compared with other authors who perform the same procedure but apply other optimization algorithms. The results show an improvement in the steady-state error in the plant response.

Moth−flame optimization (MFO) is a prominent swarm intelligence algorithm that demonstrates sufficient efficiency in tackling various optimization tasks. However, MFO cannot provide competitive results for complex optimization problems. The algorithm sinks into the local optimum due to the rapid dropping of population diversity and poor exploration. Hence, in this article, a migration-based moth−flame optimization (M-MFO) algorithm is proposed to address the mentioned issues. In M-MFO, the main focus is on improving the position of unlucky moths by migrating them stochastically in the early iterations using a random migration (RM) operator, maintaining the solution diversification by storing new qualified solutions separately in a guiding archive, and, finally, exploiting around the positions saved in the guiding archive using a guided migration (GM) operator. The dimensionally aware switch between these two operators guarantees the convergence of the population toward the promising zo... [more]

The aromatic herb lemon myrtle is a good source of polyphenols, with high antioxidant and antimicrobial capacity. In this study, the green extraction technique microwave-assisted extraction (MAE) was applied and the extraction parameters were optimized using response surface methodology (RSM) to maximize the extraction yield of phenolic compound and antioxidant properties. Then, it was compared with other popular novel and conventional extraction techniques including ultrasound-assisted extraction (UAE) and shaking water bath (SWB) to identify the most effective technique for extraction of phenolic compounds from lemon myrtle. The results showed that the MAE parameters including radiation time, power, and sample to solvent ratio had a significant influence on the extraction yield of phenolic compounds and antioxidant capacity. The optimal MAE conditions were radiation time of 6 min, microwave power of 630 W, and sample to solvent ratio of 6 g/100 mL. Under optimal conditions, MAE dry e... [more]

Process Intensification (PI) is a vast and growing area in Chemical Engineering, which deals with the enhancement of current technology to enable improved efficiency; energy, cost, and environmental impact reduction; small size; and better integration with the other equipment. Since process intensification results in novel, but complex, systems, it is necessary to rely on optimization and control techniques that can cope with such new processes. Therefore, this review presents some advancements in the field of process intensification that are worthy of exploring in detail in the coming years. At the end, several important open questions that can be taken into consideration in the coming years are listed.

Autographa californica nucleopolyhedrovirus is a very productive expression vector for recombinant proteins in insect cells. Most vectors are based on the polyhedrin gene promoter, which comprises a TAAG transcription initiation motif flanked by 20 base pairs upstream and 47 base pairs downstream before the native ATG. Many transfer vectors also include a short sequence downstream of the ATG, in which case this sequence is mutated to ATT to abolish translation. However, the ATT sequence, or AUU in the mRNA, is known to be leaky. If a target-coding region is placed in the frame with the AUU, then some products will comprise a chimeric molecule with part of the polyhedrin protein. In this study, we showed that if AUU is placed in the frame with a Strep tag and eGFP coding region, we could identify a protein product with both sequences present. Further work examined if alternative codons in lieu of AUG might reduce translation initiation further. We found that AUA was used slightly more e... [more]

A novel method proposed to choose the optimal working fluid—solely from the point of view of expansion route—for a given heat source and heat sink (characterized by a maximum and minimum temperature). The basis of this method is the novel classification of working fluids using the sequences of their characteristic points on temperature-entropy space. The most suitable existing working fluid can be selected, where an ideal adiabatic (isentropic) expansion step between a given upper and lower temperature is possible in a way, that the initial and final states are both saturated vapour states and the ideal (isentropic) expansion line runs in the superheated (dry) vapour region all along the expansion. Problems related to the presence of droplets or superheated dry steam in the final expansion state can be avoided or minimized by using the working fluid chosen with this method. Results obtained with real materials are compared with those gained with model (van der Waals) fluids; based on t... [more]

In order to study the contribution of each harmonic to the output torque and axial torque of the axial magnetic gear with Halbach permanent magnet arrays (HAMG), torque and axial force calculation formulas of the HAMG are proposed based on the air-gap flux density distribution of the HAMG. Because of the difference of the air-gap flux densities at different radii, two simplified torque and axial force calculation formulas are proposed and compared. To improve the torque capability of the HAMG, parametric analysis of eight dimensional parameters is firstly conducted. By parametric analysis, six parameters such as the inner radius have been found to have obvious impact on the output torque and output torque density of the HAMG. The optimization using Maxwell software is then executed for maximizing the output torque density of the HAMG. The output torque density of the optimized HAMG is improved from 78.1 kNm/m3 to 93.3 kNm/m3 with an increase of 19%. Furthermore, spectrum analysis is al... [more]

A data-driven workflow approach is presented in this study for optimizing fracture spacing of multifractured horizontal wells (MFHW) in shale oil reservoirs. The workflow employs a simple well productivity model for the initial design of hydraulic fracturing well completions. This provides a transparent approach to the identification of key fracturing parameters affecting well productivity. The workflow uses transient pressure or production data to identify fracture interference. This offers a reliable and cost-effective means for assessment of well production potential in terms of optimization of fracture spacing in the MFHW. Result of a field case study indicated that three wells were drilled in an area with dense natural fractures, and the fracture spacing of MFHW in this area was short enough to effectively drain the stimulated reservoir volume (SRV), while the other three wells were drilled in an area with less natural fractures, and the fracture spacing of MFHW in this area could... [more]

The paper presents issues of optimisation of a wind power plant−energy storage system (WPP-ESS) arrangement operating in a specific geographical location. An algorithm was developed to minimise the unit discounted cost of electricity generation in a system containing a wind power plant and flywheel energy storage. In order to carry out the task, population heuristics of the genetic algorithm were used with modifications introduced by the author (taking into account the coefficient of variation of the generation in the quasi-static term of the penalty and the selection method). The set of inequality restrictions related to the technical parameters of turbines and energy storage and the parameters of energy storage management has been taken into account with the application of the Powell−Skolnick penalty function (Michalewicz modification). The results of sample optimisation calculations for two wind power plants of 2 MW were presented. The effects achieved in the process of optimisation... [more]

Recovering energy from waste energy sources is an important issue as environmental pollution and the energy crisis become serious. In the same context, recovering liquefied natural gas (LNG) cold energy from an LNG-powered ship is also important in terms of energy savings. To this end, this study investigated a novel solution for a LNG-powered ship to recover LNG cold energy. Six different organic Rankine cycle (ORC) systems (three for high-pressure dual-fuel engines and three for medium-pressure dual-fuel engines) were proposed and optimized; nine different working fluids were investigated; annualized costs for installing proposed ORC systems were estimated based on the optimization results. In addition, a sensitivity analysis was performed to identify the effect of uncertainties on the performance of the ORC systems. As a result, the ORC system for the medium-pressure engines with direct expansion, multi-condensation levels, and a high evaporation temperature exhibited the best perfo... [more]

Hybrid electric vehicles (HEVs) require supervisory controllers to distribute the propulsion power from sources like an engine and motors. Control concepts based on optimal control theories such as dynamic programming (DP) and Pontryagin’s minimum principle (PMP) have been studied to maximize fuel efficiencies. These concepts are, however, not practical for real-world applications because they guarantee optimality only if future driving information is given prior to the actual driving. Instead, heuristic rule-based control concepts are widely used in real-world applications. Those concepts are not only simple enough to be designed based on existing vehicle control concepts, but also allow developers to easily intervene in the control to enhance other vital aspects of real-world vehicle performances, such as safety and drivability. In this study, a rule-based control for parallel type-2 HEVs is developed based on representative control concepts of real-world HEVs, and optimal control pa... [more]

In this paper, a systematic analysis of seven control topologies is performed, based on three possible control variables of the power generated by the Fuel Cell (FC) system: the reference input of the controller for the FC boost converter, and the two reference inputs used by the air regulator and the fuel regulator. The FC system will generate power based on the Required-Power-Following (RPF) control mode in order to ensure the load demand, operating as the main energy source in an FC hybrid power system. The FC system will operate as a backup energy source in an FC renewable Hybrid Power System (by ensuring the lack of power on the DC bus, which is given by the load power minus the renewable power). Thus, power requested from the batteries’ stack will be almost zero during operation of the FC hybrid power system based on RPF-control mode. If the FC hybrid power system operates with a variable load demand, then the lack or excess of power on the DC bus will be dynamically ensured by t... [more]

Small-scale decentralized polygeneration systems have several energetic, economic and environmental benefits. However, using multiple energy sources and providing multiple energy services can lead to complicated studies which require advanced optimization techniques for determining optimal solutions. Furthermore, several parameters can influence the design and performance of a polygeneration system. In this study, the effects of heat load, renewable generation and storage units on the optimal design and performance of a polygeneration system for a hypothetical hospital located in northern Italy are investigated. The polygeneration system shows higher performance compared to the reference system, which is based on the separate generation of heat and power. It reduces fuel consumption by 14⁻32%, CO₂ emissions by 10⁻29% and annualized total cost by 7⁻19%, for various studied scenarios. The avoided fuel and electricity purchase of the polygeneration system has a positive impact on the econ... [more]

This paper proposes a driving-scenario oriented optimal design of an axial-flux permanent-magnet (AFPM) motor for an electric vehicle. The target torque and speed (TN) curve is defined as three operation zones-constant torque, maximum direct current, and maximum voltage—based on the driving scenario. The AFPM motor is designed to minimize energy consumption based on the motor weight and the frequent operating points of a driving cycle. The final result shows that the electric vehicle driven by the proposed AFPM motor consumes about 15% less energy than motors designed using traditional methods.

Deployment of photovoltaic (PV) systems has recently been encouraged for large-scale and small-scale businesses in order to meet the global green energy targets. However, one of the most significant hurdles that limits the spread of PV applications is the dust accumulated on the PV panels’ surfaces, especially in desert regions. Numerous studies sought the use of cameras, sensors, power datasets, and other detection elements to detect the dust on PV panels; however, these methods pose more maintenance, accuracy, and economic challenges. Therefore, this paper proposes an intelligent system to detect the dust level on the PV panels to optimally operate the attached dust cleaning units (DCUs). Unlike previous strategies, this study utilizes the expanded knowledge and collected data for solar irradiation and PV-generated power, along with the forecasted ambient temperature. An expert artificial intelligence (AI) computational system, adopted with the MATLAB platform, is utilized for a high... [more]

Since existing energy system models often represent storage behavior in a simplified way, in this work, a tool chain for deriving consistent storage model parameters for optimization models is developed. The aim of our research work is to identify what are non-negligible influences on the the technical characteristics and dynamic behavior of the storage, to quantify the effect of these influences, and represent these effects in the model. This paper describes the developed tool chain and presents its application using an example. The tool chain consists of the steps “parameter screening”, “dynamic simulation”, “regression analysis” and “refining optimization model”. It is investigated which parameters have an influence on the storage system (here pumped hydroelectric energy storage (PHES)), how the storage behavior is modeled, which influencing factors have a measurable effect on the system, and how these findings can be integrated into optimization models. The main finding is that in... [more]