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- Using System Dynamics for Simulation and Optimization of an Investment
Decision System Under Uncertainty-
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Abstract: Financial problems have been the subject of many researches. Taking into account investment and having the best portfolio, selecting the best subsidiary companies for investment has long been important and inevitable for various holding companies. Since appropriate investing decisions lead to profitability of these giant companies, evaluation and selection of subsidiary companies before making the investment are important for the holding companies. In this study, a system dynamic model is presented for investment on the decision system. The problem consists of a holding company as a main organization that invests in different subsidiary companies, where each of them also invests in different projects. The holding company and the subsidiary companies may invest in different time periods. This investing system has been modeled and simulated with the help of system dynamics (SD) approaches. According to the results of simulation, the holding company decides to invest in which subsidiary company. In fact, the simulation helps the holding company attain the best portfolio selection. Finally, a simulation result is presented to illustrate both efficiency and effectiveness of the proposed investment model, and effectiveness of the variables was assessed using sensitivity analysis. Also, the validity of model has been considered. PubDate: 2022-06-01
- Application of Whale Optimization Technique for Evaluating the Performance
of Wind-Driven PMSG Under Harsh Operating Events-
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Abstract: Permanent magnet synchronous generators (PMSGs) have become a promising alternative for wind energy generation systems (WEGSs) because of their optimal power extraction, complete controllability, and improved power quality. The growing penetration of PMSG-based WEGSs into the electrical power system has made its performance analysis an imperative field of research. In this paper, detailed mathematical models for a wind turbine, PMSG, power converters, control system, and grid model are used to study the dynamic behavior and operation of the PMSG-based WEGSs. Optimal torque control is used to operate the wind system at maximum power point tracking (MPPT); in addition, whale optimization algorithm-based PI controllers are utilized for the current control of the machine side converter. Furthermore, a hysteresis controller-based braking chopper system is utilized to improve the fault ride-through (FRT) capability and to keep DC-link voltage within its permissible limits. Two scenarios are studied to evaluate the transient and dynamic response of the system. The first scenario exposes the studied system to a regular grid condition (step-change and random variations in the wind speed profile), while the second scenario exposes it to an irregular grid operation (single-phase and three-phase faults). MATLAB/SIMULINK environment is used to validate the effectiveness and superiority of the proposed control schemes during the studied scenarios. The obtained simulation results assure the viability of the overall proposed system and control schemes in improving the power smoothing capability and dynamic response of the system parameters in addition to operating the wind system at MPPT and realizing the FRT capability. Moreover, keeping a constant DC-link voltage is one of the benefits that would result in increasing the life span of the power converters and reducing the amount of cut-off time of the whole system that may otherwise be caused by their destruction. PubDate: 2022-06-01
- Flexible Job Shop Scheduling for Press Working Industries with Operation
Precedence Constraint-
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Abstract: To remain sustainable, the press working industries must be energy efficient, should ensure minimum material waste and should employ solutions for Industry 4.0 using artificial intelligent techniques. In this work, an attempt is therefore made to solve the real-life problem of press working industry which is related to flexible job shop scheduling problem considering sustainability aspect. This is done by minimising the number of hours required to operate the system for a given lot size and thus making the overall system energy efficient. A mathematical model is developed considering waiting time on machines along with production time and setup time. To solve this model, discrete version of a one of the well-known metaheuristics namely artificial bee colony algorithm has been employed. The results show that there is a significant saving in total time of 10.71% over that by existing practice of the particular industry. It also means that production machines will run 10.71% less for the given lot size resulting into saving of same amount of energy. Also due to material flow optimisation, the energy consumed by material handling devices is also less. Graphical abstract  PubDate: 2022-06-01
- Vendor-Buyer Pollution Sensitive Inventory System for Deteriorating Items
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Abstract: With the rapid development of sustainable implements, supply chain members are interested in executing well, not only economically but also environmentally. It is widely recognized today that the preservation technology investment for deteriorating items in production inventories paid much attention in inventory management because most of the physical goods deteriorate over time. The present study develops an integrated vendor-buyer production inventory model for deteriorating items by considering environmental pollution due to production. Moreover, the deterioration calls for effective practices to curb the consequent losses for which an investment in preservation technology is considered. The objective of the proposed study is to optimize preservation technology investment, the number of shipments, and shipment quantity, which minimizes the total cost of the supply chain per unit time. Also, the individual’s total costs of vendor and buyer are taken into account. The robustness of the proposed model is demonstrated by a numerical example. Sensitivity analysis is carried out to establish key model features. Moreover, managerial implications are given to extract significant insights from the model. The investment in preservation technology is deliberated as a decision variable to control the deteriorated inventories of the system. Total cost is highly sensible with respect to scale demand, buyer’s holding cost, buyer’s variable shipping cost, and rate of pollution absorption by the nature. As buyer’s holding cost increases the total cost which is not encouraging because organization does not want to store too much inventory when holding cost or deterioration is high, whereas the vendor’s holding cost has managerial impact on the total cost. PubDate: 2022-06-01
- Single-Machine Multi-feedstock Sustainable EPQ Models for a Biomass
Direct-Fired Power Plant with Non-zero Setup Times-
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Abstract: This paper develops three production inventory models for a biomass direct-fired power plant. Together these three models enable a portfolio selection for a biomass direct-fired power plant’s production and inventory policies. In general, the models facilitate any production system that can process multiple heterogeneous kinds of feedstocks in a single machine to produce identical output. Model 1.1 develops inventory policies for a power plant that uses biomass feedstocks in solitary forms. This model also considers supply constraints and single bulk procurement of biomass items. Model 1.2 varies from Model 1.1 by relaxing the supply constraints and single bulk procurement mode. Model 2 develops inventory policies for a power plant that uses biomass blends as feedstock in all production cycles. Models 1.1 and 1.2 are optimized using Karush-Kuhn-Tucker (KKT) conditions. Model 2 is optimized using a genetic algorithm. The models are evaluated using numerical examples and compared based on various cost components. The proposed models’ suitability is explained based on the power plant’s geographical location and procurement policies. The results show that the efficiency of a biomass blend has a vital role in minimizing the annual costs. The cost components and efficiencies collectively determine the proportion of each biomass item in the biomass blend. Biomass blend has a higher efficiency than that of the individual feedstocks. Annual production setup cost reduces significantly when biomass blend is used in the production process. Therefore, Model 2 incurs a lower annual total cost than Models 1.1 and 1.2. PubDate: 2022-06-01
- A Manufacturer-Retailer Inventory Model with Remanufacturing, Stochastic
Demand, and Green Investments-
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Abstract: This paper develops an integrated inventory model for a closed-loop supply chain (CLSC) system consisting of a manufacturer and a retailer. The demand and the returns of used products are assumed to be stochastic in nature. A carbon tax policy is implemented to cut down the emissions from transportation, production, and storage. To lessen the emissions from the operations, the manufacturer invests in green technologies. In addition, the take-back investment is also done by the manufacturer to increase the number of returned products collected from the market. A mathematical model is proposed to minimize the joint total cost incurred by the supply chain. An iterative procedure is employed to find the optimal values of the number of shipments, amount of investments, safety factor, shipment quantity, and the collection rate. A numerical example and a sensitivity analysis are presented to show the application of the model and to investigate the influence of key parameters on the performance of the model. The results show that by adjusting the production rate flexibly and setting the appropriate level of collection rate, the supply chain can maintain the emissions and cost. Furthermore, the green investment and take-back investment can be used as mechanism to cut down the emissions and to manage the requirement of used product in the production process. PubDate: 2022-06-01
- Evaluation of Municipal Solid Waste Management Scenarios using
Multi-Criteria Decision Making under Fuzzy Environment-
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Abstract: Treatment of municipal solid waste in India is facing a grave crisis, where merely 25% of waste is treated per day. There is a desperate need for efficient as well as compatible options for the proper management of solid waste, which otherwise causes not only health problems but also creates social trouble. Therefore, there is a requirement of determining suitable treatment technology for respective waste material among its available options. In this study, various commonly used municipal solid waste management techniques are identified, investigated, and further different criteria are selected to evaluate them. Eight solid waste management scenarios are formed using core municipal solid waste management techniques such as landfill, incineration, biomethanation, composting, recycling and reuse, and aerobic digestion. The scenarios are evaluated using nine criteria, which are classified into four major categories as environmental, social, financial, and profitable criteria. The criteria are finalized, and their weights are determined by utilizing the data collected as per the opinions of the experts from relevant domains and weighted using the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) technique. The data is collected by way of questionnaires for various solid waste management techniques. Then, a Multi-Criteria Decision Making (MCDM) method, namely the Fuzzy Technique for Order Preferences by Similarity to Ideal Solutions (Fuzzy TOPSIS) approach is applied for ranking of the different treatment waste management scenarios. The result of this study shows that 40% Biomethanation + 60% Landfill is the best scenario among the available methodologies of solid waste management. This study would help in determining the suitable treatment technology for Municipal Solid Waste (MSW) material. All stakeholders including civic organizations, government bodies, society as a whole, would be able to understand the various techniques and tools used in the study and hence make judgments. PubDate: 2022-06-01
- Optimal Static Var Compensator Switching in Unbalanced Distribution System
Based on Artificial Neural Network-
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Abstract: The rising incidence of equipment mal-operations and failures due to inadequate reactive power compensation facilities at power distribution centers is an increasing concern everywhere. The distribution static compensator (DSTATCOM) is the best solution for this issue. However, they can be very costly and complex to use. In this case study, the static var compensator (SVC) is used in a thyristor binary switched capacitors (TBSC)-thyristor-controlled reactor (TCR) configuration. The TCR in SVC, while correcting, produce harmonics intrinsically due to non-sinusoidal currents. The purpose of this study is to investigate the connection between unbalanced load with poor reactive power management and harmonic mitigation facility in a power distribution network. The optimal size reactor and the binary sequence of the capacitor banks are considered. The artificial neural network (ANN) approach is used to solve a nonlinear problem and calculate the optimal firing delay angle used to switch thyristors in TCR with accurate delay to reduce harmonic distortion significantly. The proposed strategy is appealing and can be used for the steady-state reactive power allocation in SVC applications in distribution networks. PubDate: 2022-06-01
- Development of One-dimensional Semi-coupled Field Electromagnetic-Thermal
Model on Electromagnetic Tube Forming-
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Abstract: Electromagnetic forming is an impulse or high speed forming technology using a pulsed magnetic field to apply Lorentz forces to parts preferably made of a highly electrically conductive material with no mechanical contact and no working medium. Thus, the hollow sections can be compressed or expanded and flat or preformed three-dimensional sheets can be shaped and assembled as well as cutting operations can be performed. Although electromagnetic forming has been a known technology for several decades, a current revival of interest is brought to its industrial application, favored by its potential to form aluminum and copper alloys and other materials with low formability. Along with this interest, the demand for simulation tools is increasing. The main achievement of this research is to present a simple and accurate theoretical model that can provide a bridge between electrical data and thermal data in the process of electromagnetic tube forming. The proposed model estimates the temperature of the workpiece faster than finite element or experimental models. The present research aims to develop one-dimensional theoretical model of a semi-coupled electrothermal field for the analysis of electromagnetic tube forming. The electromagnetic forming process divided into two sub-models that are solved together: Based on Maxwell’s equations electromagnetic model, and linked thermomechanical part behavior model. In this work, special attention is devoted to the study of the most relevant process parameters, with emphasis on their meaning, effects, and mutual interaction. To assess the performance of the proposed approach, the results are compared with the finite element method-ANSYS tool and experimental data, in order to assess the robustness and precision of the proposed model. The results obtained show a good correlation between the proposed theoretical model than the numerical values and experimental data by 7% difference, making it possible to validate the methodology developed. PubDate: 2022-06-01
- Energy and Economic Analysis of Methanol Synthesis Using Reactive
Distillation-
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Abstract: Methanol production using reactive distillation (RD) is compared with the conventional process that uses a packed bed reactor and the three phase process involving a slurry reactor (SR). The RD column design was developed using a new methodology to remove the exothermic heat of reaction and overcome the equilibrium limitations. Both the conventional and RD-based processes are comparable in terms of the reactant conversions and production (~ 487 TPD and ~ 491 TPD, respectively), though the conventional process offers better methanol productivity (25.5 mol/(kg.h) vs. 14.8 mol/(kg.h) in case of RD). The SR based process has the lowest conversions of reactants and methanol production (~ 483 TPD) among the three processes, though its productivity is comparable to the RD based process. Though all the processes were self-sufficient in their energy requirements, the process involving the SR had the highest surplus power production of ~ 1.6 MW. The energy efficiency of both the processes was ~ 80% (syngas to methanol). In terms of the economics, the SR-based process has the lowest NPV and IRR due to higher production costs and low methanol production. The RD-based process has higher capital and operating costs leading to a lower net present value (NPV), internal rate of return (IRR), and greater payback period compared to the conventional PBR process. The RD-based process offered economic feasibility over a limited range in comparison with the conventional process, which exhibited economic viability over a wider range of raw material (syngas) costs and product (methanol) prices. PubDate: 2022-06-01
- Environmental Sustainability Framework for Plastic Waste Management—a
Case Study of Bubble Tea Industry in Malaysia-
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Abstract: Economic growth and rapid industrialisation have led to enormous increase in municipal solid waste (MSW). Lack of waste management alternatives and ineffective waste policy implementation are the major challenges for government to materialise a sustainable solid waste management framework, especially for plastic waste. Booming of the food and beverage (F&B) industry has aggravated the situation by generating more plastic waste with no economic values. Hence, this study aims to evaluate the overall environmental performance of existing and alternative waste management technologies that are available in Malaysia based on net greenhouse gas (GHG) emission in terms of carbon dioxide equivalent (kg CO2-eq) per tonne of plastic waste that are analysed through life cycle assessment (LCA) methodology. LCA result has proven that Scenario B (waste to energy (WTE) incineration) is more environmentally preferable as it had a negative net GHG emission of − 573.80 kg CO2-eq as compared to GHG emission of existing Scenario A (sanitary landfill) of 566.15 kg CO2-eq. Negative net GHG emission in WTE incineration was mainly due to higher GHG saving achieved through cleaner electricity generation as compared to conventional power production. This alternative technology was proven to have the potential to reduce the dependence on landfills and is served as the basis of environmental sustainability framework development for plastic waste management based on case study in Malaysia. This framework can be served as the baseline for the local authorities or policy makers for other plastic waste generation hotspots other than bubble tea industry to improve plastic waste management via WTE incineration. PubDate: 2022-06-01
- Incorporating Health Considerations in Water Minimisation
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Abstract: As climate change escalates, there is a need for proper planning of future use of water resources. The occurrence of prolonged droughts and fluctuation of weather patterns can lead to serious water scarcity issues. Process integration techniques have been widely used for water management in the process plants. This paper extends the insight-based and mathematical programming techniques of process integration to incorporate health aspects in water management. In particular, health quality index is used as a quality metric in considering water recovery in a system of processes. The consideration of health aspects is important for cases involving direct contact of human body with water, such as in water recreational activities. In addition, multi-period planning (MPP) is also considered in this work, where water recovery takes place across different periods. A representative water park case study is used to illustrate the applicability of the proposed method. PubDate: 2022-06-01
- Techno-economic Evaluation of Municipal Solid Waste–Fueled Biogas
Generator as a Backup in a Decentralized Hybrid Power System-
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Abstract: This study investigates the technical and economic viability of using municipal solid waste–fueled biogas generator as a backup in a hybrid power system comprising solar photovoltaic, a battery bank, and a bi-directional converter. Hybrid Optimization Model for Electric Renewables (HOMER) was used for the simulation, optimization, and sensitivity analysis of the proposed standalone model for a remote Igu village in Nigeria. The results of the optimal hybrid system ranked according to the least net present cost indicate that with an average municipal solid waste generation of 86.76 tons/day as feedstock for biogas generator and solar insolation of 5.45 kWh/m2/day, the proposed hybrid power system is capable of meeting the electricity demands of 2,822.20 kWh/day of the isolated community. This optimal system comprises a 500 kW biogas generator, 800 kW photovoltaic panels, a 400 kW converter, and 5,000 strings of battery and has a net present cost of $8,510,723.00, levelized cost of energy of $0.2917/kWh, and an operating cost of $182,934.00 per year. The integration of municipal solid waste resources also leads to the emission of 0.974 kg/year of nitrogen oxide, 140 kg/year of carbon dioxide, and 1.56 kg/year of carbon monoxide. The performance of the optimal system was not affected when the biogas generator feedstock was the sensitivity variable. However, the system’s annual power generation increased, while the net present cost, levelized cost of energy, operating cost, and carbon emission decreased with increased photovoltaic penetration. PubDate: 2022-06-01
- Simulation and Optimization of Operating Conditions of a Packed Bed
Reactor for Acrylonitrile Production from Propene Ammoxidation over $$\alpha$$ α -Bismuth Molybdate-
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Abstract: Propene ammoxidation is a complex reaction with acrylonitrile (ACN) as a desired product and several undesired products such as CO2 and CO. Optimization of this process is important to meet the sustainable development goals by reducing the generation of greenhouse gasses and energy required to purify ACN. In this work, propene ammoxidation over \(\alpha\) -bismuth molybdate in a packed bed reactor (PBR) is simulated with Mathematica to maximize the ACN yield. A system of ordinary differential equations (ODEs) is set based on kinetics and mechanism of propene ammoxidation. Four different levels of temperature, pressure, oxygen to propene ratio, water to propene ratio, and pellet size are selected. Then, 16 runs are defined based on the modified \({L}_{16}\) orthogonal array of Taguchi method and the system of ODEs is run to find the mole flow rates of all species and pressure drop. These results are used to maximize the ACN yield using the analysis of variance and signal to noise ratios. The results indicate that temperature and pellet size are, respectively, the most and the least important parameters to maximize the ACN yield. The PBR must work under the maximum possible temperature and minimum possible pressure. Using the optimum operating conditions, an overall propene conversion of 98% and acrylonitrile yield of 76% is achieved. PubDate: 2022-06-01
- Economic Pinch Analysis for Estimating Service Life
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Abstract: Economic appraisal is essential for firms to identify and quantify the monetary costs and benefits of investment in a particular asset meant to provide a service over its physical lifetime and achieve economic sustainability. Use of such a service-providing asset for extended period results in performance deterioration and customer dissatisfaction with the enhanced service cost. Standard measures of economic appraisal fail to provide a criterion for the period of ownership of assets that do not generate an income but provide valuable service. The economic service life is a measure that can gauge the profitability of an investment and the period of useful ownership for such an asset. This paper extends the economic pinch analysis method for estimating the economic service life of an asset. A graphical representation of composite cash flows on a time domain embodies the economic appraisal parameters like the net present cost, the annual worth, and the economic service life of an asset. Novel graphical representations of composite cash flows, complemented with tabular computation methods, are represented to determine the economic service life. The utility of the recommended economic pinch analysis is shown through three illustrative examples. The procedure’s usefulness is demonstrated for an equipment replacement analysis problem. The proposed approach is applicable to determine the economic evaluation of any service-providing asset and helps industries achieve economic sustainability by choosing the period of ownership. PubDate: 2022-06-01
- Modelling Stakeholder Goals in Industrial Symbiosis
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Abstract: Industrial symbiosis is one of the mechanisms to achieve a more sustainable industrial ecosystem. It promotes the establishment of waste and by-product exchange between independently operating industries to reduce the generation of waste and the consumption of virgin resources. Some of these networks have evolved organically; however, there have been attempts to engineer the industrial system to catalyze their formation. The challenge is in creating mechanisms which not only encourage industries to participate but also achieve environmental goals. Modelling stakeholder goals in the design of industrial symbiotic networks (ISNs) is critical in identifying feasible and sustainable networks. This work reviews the different approaches used for modelling stakeholder objectives in ISNs. The literature shows that integrating game theoretic principles in modelling stakeholder objectives either to determine the optimal design of the network or to simulate how the network evolves provides conditions which can be used as starting points for drafting agreements and contracts between network participants. PubDate: 2022-06-01
- Electrical Discharge Machining of Engineered Al-22%SiC Metal Matrix
Composite: Surface Roughness Analysis, Optimization, Economic Analysis, and Sustainability Assessment-
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Abstract: This research addresses electrical discharge machining of engineered Al-22%SiC metal matrix composite to analyze the surface roughness of machined part. A series of machining trials are performed under varied process conditions (flushing pressure, gap voltage, pulse-on time, discharge current, pulse-off time) obtained by Box–Behnken design. Additionally, this work addresses on desirability optimization methodology and predictive modeling for minimization of machined surface quality employing response surface methodology. Based on the motivational viewpoint of “Go green-Think green-Act green,” a unique approach has been suggested for economic analysis and sustainability assessment to determine the overall machining cost per part and to justify the usefulness of vegetable oil as dielectric medium in electrical discharge machining. According to statistical analysis, the contribution of spark discharge current was identified as the leading factor in surface quality degradation. The estimated optimal surface roughness of 0.181 µm and the calculated overall machining cost per part of Rs.245.9 were preferred at a pulse-on time of 100 µs, gap voltage of 1 V, pulse-off time of 30 µs, discharge current of 4 A, and flushing pressure of 0.57 kgf/cm2, which indicates techno-economically viable. The vegetable oil considered as dielectric fluid is biodegradable and environmentally safe, thus contributing to sustainable production. PubDate: 2022-06-01
- Energy Management in Distribution System Using Volt-VAr Optimization for
Different Loading Conditions-
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Abstract: In the current scenario, the major challenge among power utilities is to meet an exponential rise in energy demand. The major portion of increased demand is still fulfilled by coal-based power generators that impose a lot of security threats due to the exhaustible nature of fossil fuels, increased carbon footprints, negative environmental impacts like increased pollution level, environmental temperature rise and global warming. Therefore, the power utilities throughout the globe are adopting energy management techniques to tackle different issues related to supply–demand mismatching, hikes in energy prices and energy securities. Volt-VAr control is a widely used energy management technique that optimally coordinates voltage and VAr injection. Optimal reduction of a voltage produces a significant reduction in power consumption for voltage-dependent loads, which constitutes the major portion of the distribution system load. The VAr injection also ensures energy savings due to the compensation effect. Therefore, this article presented an algorithm for energy management through Volt-VAr optimization. To estimate energy savings using the proposed technique, different case studies have been considered and have been validated using IEEE 33 node system. Simulation results show that significant demand reduction during peak loading condition is possible through deeper voltage reduction while applying the proposed Volt-VAr control technique. Furthermore, the proposed technique also ensures reduction in total energy demand, line loss minimization, energy savings, power factor correction, capacity release and improvement in voltage profile. PubDate: 2022-06-01
- Multi-echelon, Multi-period Supply Chain Master Planning in the Food
Process Industry: A Sustainability Concept-
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Abstract: This work presents a multi-echelon, multi-period supply chain master planning in the process industry; with a concept of sustainability, carried out on a real-life case study located in Port Harcourt in the South–South region of Nigeria. A supply chain master panning model (SCMPM) takes into account the most effective and efficient method to fulfil customer order and demand over a mid-term planning horizon; it also takes of bottlenecks by assigning demands to production. A mixed integer, multi-objective optimization deterministic model was formulated which aimed at minimizing the overall system costs, emissions, social factors and customers order fulfilment in the supply chain. The Cplex solver of GAMS, with branch and cut algorithm, was used on an Intel processor with 2.30 GHz speed to run the model. The results obtained from the model with real industry data from the case study gave the objective function values as 324, 854, 340 Naira for economic factor, 26.455 tonnes of CO2 emission (170.50 g CO2), for environmental factor, while those of the social factor and allowable backorder gave 10.433 and 105 units of product, respectively. The results showed the feasibility of the formulated models and the importance to have an effective master planning supply chain decision model in place. A significant correlation between four conflicting objectives was achieved by using the weighted-sum approach and the analytic hierarchy process (AHP) thereby converting them to a single linear optimization model. PubDate: 2022-06-01
- Constrained Laplacian Biogeography-Based Optimization for Economic Load
Dispatch Problems-
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Abstract: Abstract Increasing price and lack of availability of fuels are the reason for the economic use of power. Economic load dispatch (ELD) problem is widely studied problem in electrical engineering, wherein the optimal output of units of generators is to be determined so on meet the specified load demand with minimal cost of fuel and emission. The complexity of the problem occurs due to various limitations. In this paper, four models of ELD problems based on different objective functions and constraints are considered. These four test problems are solved using a new variant of nature-inspired optimization technique, namely, Laplacian biogeography-based optimization algorithm. Optimal results obtained by this algorithm are then compared with its other counterparts like sine cosine algorithm, grey wolf optimization, and particle swarm optimization. While comparing with the previous results recorded, constrained LX-BBO proves its superiority over other traditional and nature-inspired optimization techniques. Due to the simplicity of LX-BBO and fewer parameters to control, it is easier to apply for real-life problems. The statistical tests are incorporated to strengthen the claim. Further algorithm complexity of the proposed algorithm is also tested. PubDate: 2022-03-08 DOI: 10.1007/s41660-022-00227-5
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