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Journal articles on the topic 'Optimisation MINLP'

Author: Grafiati

Published: 8 June 2024

Last updated: 31 July 2025

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1

Epelle, Emmanuel I., and Dimitrios I. Gerogiorgis. "A computational performance comparison of MILP vs. MINLP formulations for oil production optimisation." Computers & Chemical Engineering 140 (September 2020): 106903. http://dx.doi.org/10.1016/j.compchemeng.2020.106903.

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Diaby, Abdullatif Lacina, Lee Luong, Amer Yousef, and Jonas Addai Mensah. "A Review of Optimal Scheduling Cleaning of Refinery Crude Preheat Trains Subject to Fouling and Ageing." Applied Mechanics and Materials 148-149 (December 2011): 643–51. http://dx.doi.org/10.4028/www.scientific.net/amm.148-149.643.

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Refinery crude preheat train (CPHT) is prone to fouling and ageing effects due to the complexity of processed crude feedstock preheated prior to distillation. This has serious implications on the thermal and hydraulic performance of the CPHT. As a result, efficient performance of crude preheat trains is compromised and as such, optimal scheduling cleaning operations are required to restore performance. In this paper, we attempt to review the subject of fouling/ageing control and mitigation in crude preheat train network by optimal scheduling cleaning approach. Three prominent optimisation tech

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Savola, Tuula, and Carl-Johan Fogelholm. "MINLP optimisation model for increased power production in small-scale CHP plants." Applied Thermal Engineering 27, no. 1 (2007): 89–99. http://dx.doi.org/10.1016/j.applthermaleng.2006.05.002.

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Yusuf, Noor, and Tareq Al-Ansari. "Current and Future Role of Natural Gas Supply Chains in the Transition to a Low-Carbon Hydrogen Economy: A Comprehensive Review on Integrated Natural Gas Supply Chain Optimisation Models." Energies 16, no. 22 (2023): 7672. http://dx.doi.org/10.3390/en16227672.

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Natural gas is the most growing fossil fuel due to its environmental advantages. For the economical transportation of natural gas to distant markets, physical (i.e., liquefaction and compression) or chemical (i.e., direct and indirect) monetisation options must be considered to reduce volume and meet the demand of different markets. Planning natural gas supply chains is a complex problem in today’s turbulent markets, especially considering the uncertainties associated with final market demand and competition with emerging renewable and hydrogen energies. This review study evaluates the latest

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Gutierrez, G., and P. Vega. "PROCESS SYNTHESIS APPLIED TO ACTIVATED SLUDGE PROCESSES: A FRAMEWORK WITH MINLP OPTIMISATION MODELS." IFAC Proceedings Volumes 35, no. 1 (2002): 393–97. http://dx.doi.org/10.3182/20020721-6-es-1901.01458.

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Savola, Tuula, Tor-Martin Tveit, and Carl-Johan Fogelholm. "A MINLP model including the pressure levels and multiperiods for CHP process optimisation." Applied Thermal Engineering 27, no. 11-12 (2007): 1857–67. http://dx.doi.org/10.1016/j.applthermaleng.2007.01.002.

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Biscos, C., M. Mulholland, M. V. Le Lann, C. J. Brouckaert, R. Bailey, and M. Roustan. "Optimal operation of a potable water distribution network." Water Science and Technology 46, no. 9 (2002): 155–62. http://dx.doi.org/10.2166/wst.2002.0228.

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This paper presents an approach to an optimal operation of a potable water distribution network. The main control objective defined during the preliminary steps was to maximise the use of low-cost power, maintaining at the same time minimum emergency levels in all reservoirs. The combination of dynamic elements (e.g. reservoirs) and discrete elements (pumps, valves, routing) makes this a challenging predictive control and constrained optimisation problem, which is being solved by MINLP (Mixed Integer Non-linear Programming). Initial experimental results show the performance of this algorithm a

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Dkhili, Nouha, David Salas, Julien Eynard, Stéphane Thil, and Stéphane Grieu. "Innovative Application of Model-Based Predictive Control for Low-Voltage Power Distribution Grids with Significant Distributed Generation." Energies 14, no. 6 (2021): 1773. http://dx.doi.org/10.3390/en14061773.

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In past decades, the deployment of renewable-energy-based power generators, namely solar photovoltaic (PV) power generators, has been projected to cause a number of new difficulties in planning, monitoring, and control of power distribution grids. In this paper, a control scheme for flexible asset management is proposed with the aim of closing the gap between power supply and demand in a suburban low-voltage power distribution grid with significant penetration of solar PV power generation while respecting the different systems’ operational constraints, in addition to the voltage constraints pr

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Tanvir, M. S., and I. M. Mujtaba. "Optimisation of design and operation of MSF desalination process using MINLP technique in gPROMS." Desalination 222, no. 1-3 (2008): 419–30. http://dx.doi.org/10.1016/j.desal.2007.02.068.

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10

Brusis, D., J. Stichlmair, and F. F. Kuppinger. "MINLP Optimisation of a Distillation/Pervaporation Process for the Separation of a Ternary Azeotropic Mixture." Chemie Ingenieur Technik 73, no. 6 (2001): 624. http://dx.doi.org/10.1002/1522-2640(200106)73:6<624::aid-cite6242222>3.0.co;2-s.

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11

Amjath, Mohamed, Laoucine Kerbache, and James MacGregor Smith. "A Closed Queueing Networks Approach for an Optimal Heterogeneous Fleet Size of an Inter-Facility Bulk Material Transfer System." Logistics 8, no. 1 (2024): 26. http://dx.doi.org/10.3390/logistics8010026.

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Background: This study addresses optimising fleet size in a system with a heterogeneous truck fleet, aiming to minimise transportation costs in interfacility material transfer operations. Methods: The material transfer process is modelled using a closed queueing network (CQN) that considers heterogeneous nodes and customised service times tailored to the unique characteristics of various truck types and their transported materials. The optimisation problem is formulated as a mixed-integer nonlinear programming (MINLP), falling into the NP-Hard, making exact solution computation challenging. A

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12

Epelle, Emmanuel I., and Dimitrios I. Gerogiorgis. "Mixed-Integer Nonlinear Programming (MINLP) for production optimisation of naturally flowing and artificial lift wells with routing constraints." Chemical Engineering Research and Design 152 (December 2019): 134–48. http://dx.doi.org/10.1016/j.cherd.2019.09.042.

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13

Tveit, Tor-Martin, and Carl-Johan Fogelholm. "Multi-period steam turbine network optimisation. Part II: Development of a multi-period MINLP model of a utility system." Applied Thermal Engineering 26, no. 14-15 (2006): 1730–36. http://dx.doi.org/10.1016/j.applthermaleng.2005.11.004.

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14

Akgul, O., N. Mac Dowell, L. G. Papageorgiou, and N. Shah. "A mixed integer nonlinear programming (MINLP) supply chain optimisation framework for carbon negative electricity generation using biomass to energy with CCS (BECCS) in the UK." International Journal of Greenhouse Gas Control 28 (September 2014): 189–202. http://dx.doi.org/10.1016/j.ijggc.2014.06.017.

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15

Smith, E. "Global Optimisation of Nonconvex MINLPs." Computers & Chemical Engineering 21, no. 1-2 (1997): S791—S796. http://dx.doi.org/10.1016/s0098-1354(97)00146-4.

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Smith, Edward M. B., and Constantinos C. Pantelides. "Global optimisation of nonconvex MINLPs." Computers & Chemical Engineering 21 (May 1997): S791—S796. http://dx.doi.org/10.1016/s0098-1354(97)87599-0.

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Andrés, Beatriz, Raquel Sanchis, Raúl Poler, Manuel Díaz-Madroñero, and Josefa Mula. "A MILP for multi-machine injection moulding sequencing in the scope of C2NET Project." International Journal of Production Management and Engineering 6, no. 1 (2018): 29. http://dx.doi.org/10.4995/ijpme.2018.8913.

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<p>The goal of C2NET European H2020 Funded Project is the creation of cloud-enabled tools for supporting the SMEs supply network optimization of manufacturing and logistic assets based on collaborative demand, production and delivery plans. In the scope of C2NET Project, and particularly in the Optimisation module (C2NET OPT), this paper proposes a novel holistic mixed integer linear programing (MILP) model to optimise the injection sequencing in a multi-machine case. The results of the MILP will support the production planner decision-making process in the calculation of (i) moulds setu

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Yang, Yuqing, Stephen Bremner, Chris Menictas, and Merlinde Kay. "A Mixed Receding Horizon Control Strategy for Battery Energy Storage System Scheduling in a Hybrid PV and Wind Power Plant with Different Forecast Techniques." Energies 12, no. 12 (2019): 2326. http://dx.doi.org/10.3390/en12122326.

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This paper presents a mixed receding horizon control (RHC) strategy for the optimal scheduling of a battery energy storage system (BESS) in a hybrid PV and wind power plant while satisfying multiple operational constraints. The overall optimisation problem was reformulated as a mixed-integer linear programming (MILP) problem, aimed at minimising the total operating cost of the entire system. The cost function of this MILP is composed of the profits of selling electricity, the cost of purchasing ancillary services for undersupply and oversupply, and the operation and maintenance cost of each co

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Saber, Takfarinas, Joao Marques-Silva, James Thorburn, and Anthony Ventresque. "Exact and Hybrid Solutions for the Multi-Objective VM Reassignment Problem." International Journal on Artificial Intelligence Tools 26, no. 01 (2017): 1760004. http://dx.doi.org/10.1142/s0218213017600041.

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Machine Reassignment is a challenging problem for constraint programming (CP) and mixed integer linear programming (MILP) approaches, especially given the size of data centres. Hybrid solutions mixing CP and heuristic algorithms, such as, large neighbourhood search (CBLNS), also struggle to address the problem given its size and number of constraints. The multi-objective version of the Machine Reassignment Problem is even more challenging and it seems unlikely for CP, MILP or hybrid solutions to obtain good results in this context. As a result, the first approaches to address this problem have

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Ji, Xiaotong, Fan Xiao, Dan Liu, Ping Xiong, and Mingnian Zhang. "Distributionally Robust Collaborative Dispatch of Integrated Energy Systems with DNE Limits Considering Renewable and Contingency Uncertainties." Elektronika ir Elektrotechnika 29, no. 3 (2023): 39–47. http://dx.doi.org/10.5755/j02.eie.33960.

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Collaborative optimisation of system reserves and utilisation of renewable energy is an efficient approach to achieving robust optimal dispatch of integrated energy systems (IES). However, conventional robust dispatch methods are often too conservative and lack the ability to consider uncertainties such as renewable energy and contingency probabilities. To address these limitations, this paper proposes a distributionally robust dispatch model that co-optimises reserves and do-not-exceed (DNE) limits while considering these uncertainties. First, a deterministic optimisation model of IES is esta

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Rai, Bharatendra K., Bimal Nepal, Angappa Gunasekaran, and Yuzhu Li. "Optimisation of process audit plan for minimising vehicle launch risk using MILP." International Journal of Procurement Management 6, no. 4 (2013): 379. http://dx.doi.org/10.1504/ijpm.2013.054742.

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22

Alvisi, S., M. Franchini, M. Gavanelli, and M. Nonato. "Near-optimal scheduling of device activation in water distribution systems to reduce the impact of a contamination event." Journal of Hydroinformatics 14, no. 2 (2011): 345–65. http://dx.doi.org/10.2166/hydro.2011.147.

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This paper proposes an innovative procedure for identifying, in the event of accidental or intentional contamination of a water distribution system, the optimal scheduling of activation of a pre-selected set of flow control devices which will serve to minimise the volume of contaminated water consumed by users after the detection of the contaminant in the system. The constraints are represented by the number of available response teams and the maximum speed at which these teams can travel along the roadway. The optimal scheduling of device activation is sought by means of an optimisation proce

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23

Schönberger, Manuel, Immanuel Trummer, and Wolfgang Mauerer. "Quantum-Inspired Digital Annealing for Join Ordering." Proceedings of the VLDB Endowment 17, no. 3 (2023): 511–24. http://dx.doi.org/10.14778/3632093.3632112.

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Finding the optimal join order (JO) is one of the most important problems in query optimisation, and has been extensively considered in research and practise. As it involves huge search spaces, approximation approaches and heuristics are commonly used, which explore a reduced solution space at the cost of solution quality. To explore even large JO search spaces, we may consider special-purpose software, such as mixed-integer linear programming (MILP) solvers, which have successfully solved JO problems. However, even mature solvers cannot overcome the limitations of conventional hardware prompt

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24

Cerchio, Marco, Francesco Gullí, Maurizio Repetto, and Antonino Sanfilippo. "Hybrid Energy Network Management: Simulation and Optimisation of Large Scale PV Coupled with Hydrogen Generation." Electronics 9, no. 10 (2020): 1734. http://dx.doi.org/10.3390/electronics9101734.

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The power production of electrical Renewable Energy Sources (RES), mainly PV and wind energy, is affected by their primary source of energy: solar radiation value or wind strength. Electrical networks with a large share of these sources must manage temporal imbalances of supply and demand. Hybrid Energy Networks (HEN) can mitigate the effects of this unbalancing by providing a connection between the electricity grid and and other energy vectors such as heat, gas or hydrogen. These couplings can activate synergies among networks that, all together, increase the share of renewable sources helpin

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25

Smith, E. M. B., and C. C. Pantelides. "A symbolic reformulation/spatial branch-and-bound algorithm for the global optimisation of nonconvex MINLPs." Computers & Chemical Engineering 23, no. 4-5 (1999): 457–78. http://dx.doi.org/10.1016/s0098-1354(98)00286-5.

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26

Pettenati, M., N. Croiset, G. Picot-Colbeaux, et al. "Optimisation of wastewater treatments through combined geomaterials and natural soil filter: modelling tools." Journal of Water Reuse and Desalination 2, no. 4 (2012): 185–93. http://dx.doi.org/10.2166/wrd.2012.023.

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The main objective of this study is the establishment of innovative purification systems through the conceptualisation of reactive barriers in soil for artificial recharge of groundwater with treated wastewater. Numerical integration of hydrodynamics and biogeochemical processes controlling the effectiveness of this engineering system is applied to design soil column experiments. This leads to the elaboration of a combined aerobic/anaerobic environment to ensure the successive nitrification of rich ammonium wastewater and the denitrification mechanisms reducing NO3– according to heterotrophic

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Veintimilla-Reyes, Jaime, Annelies De Meyer, Dirk Cattrysse, and Jos Van Orshoven. "From Linear Programming Model to Mixed Integer Linear Programming Model for the Simultaneous Optimisation of Water Allocation and Reservoir Location in River Systems." Proceedings 2, no. 11 (2018): 594. http://dx.doi.org/10.3390/proceedings2110594.

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The allocation of water flowing through a river-with-reservoirs system to optimally meet spatially distributed and temporally variable demands can be conceived as a Network Flow Optimisation (NFO) problem and addressed by Linear Programming (LP). In this paper we present an extension of the strategic NFO-LP model to simultaneously optimise the allocation of water and the location of one or more reservoirs. The applicability of the MILP model has been illustrated by applying it to a hypothetical river network configuration consisting of seven candidate reservoir nodes and seven demand nodes, an

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Tausif, Ismail. "Last mile delivery Optimisation model for drone-enabled Vehicle Routing Problem." Emerging Minds Journal for Student Research 1 (July 11, 2023): 39–73. http://dx.doi.org/10.59973/emjsr.11.

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In light of e-commerce's exponential growth trajectory over recent years, it has never been more critical to evaluate the last-mile delivery segment for its efficiency and cost-effectiveness. Autonomous vehicles (drones) offer considerable promise as potential solutions with ongoing investigations into emerging technologies in this context. To address problems related to last mile-delivery in logistics operations, the practicality of adopting a hybrid truck-drone delivery system is examined through this study. The researchers utilized Mixed-integer linear programming (MILP)and Gurobi optimizat

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Chen, Yongnan, Songsong Liu, Lazaros G. Papageorgiou, Konstantinos Theofilatos, and Sophia Tsoka. "Optimisation Models for Pathway Activity Inference in Cancer." Cancers 15, no. 6 (2023): 1787. http://dx.doi.org/10.3390/cancers15061787.

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Background: With advances in high-throughput technologies, there has been an enormous increase in data related to profiling the activity of molecules in disease. While such data provide more comprehensive information on cellular actions, their large volume and complexity pose difficulty in accurate classification of disease phenotypes. Therefore, novel modelling methods that can improve accuracy while offering interpretable means of analysis are required. Biological pathways can be used to incorporate a priori knowledge of biological interactions to decrease data dimensionality and increase th

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Liapis, Georgios I., Sophia Tsoka, and Lazaros G. Papageorgiou. "Optimisation-Based Feature Selection for Regression Neural Networks Towards Explainability." Machine Learning and Knowledge Extraction 7, no. 2 (2025): 33. https://doi.org/10.3390/make7020033.

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Regression is a fundamental task in machine learning, and neural networks have been successfully employed in many applications to identify underlying regression patterns. However, they are often criticised for their lack of interpretability and commonly referred to as black-box models. Feature selection approaches address this challenge by simplifying datasets through the removal of unimportant features, while improving explainability by revealing feature importance. In this work, we leverage mathematical programming to identify the most important features in a trained deep neural network with

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Brand, Cornelius, Martin Koutecký, and Sebastian Ordyniak. "Parameterized Algorithms for MILPs with Small Treedepth." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 14 (2021): 12249–57. http://dx.doi.org/10.1609/aaai.v35i14.17454.

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Solving (mixed) integer (linear) programs, (M)I(L)Ps for short, is a fundamental optimisation task with a wide range of applications in artificial intelligence and computer science in general. While hard in general, recent years have brought about vast progress for solving structurally restricted, (non-mixed) ILPs: n-fold, tree-fold, 2-stage stochastic and multi-stage stochastic programs admit efficient algorithms, and all of these special cases are subsumed by the class of ILPs of small treedepth. In this paper, we extend this line of work to the mixed case, by showing an algorithm solving MI

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Hong, Qiuyi, Fanlin Meng, and Jian Liu. "Customised Multi-Energy Pricing: Model and Solutions." Energies 16, no. 4 (2023): 2080. http://dx.doi.org/10.3390/en16042080.

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With the increasing interdependence among energies (e.g., electricity, natural gas and heat) and the development of a decentralised energy system, a novel retail pricing scheme in the multi-energy market is demanded. Therefore, the problem of designing a customised multi-energy pricing scheme for energy retailers is investigated in this paper. In particular, the proposed pricing scheme is formulated as a bilevel optimisation problem. At the upper level, the energy retailer (leader) aims to maximise its profit. Microgrids (followers) equipped with energy converters, storage, renewable energy so

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Infante Cuan, Jorge Eduardo, Víctor Fernández García, Reynaldo Palacios, and Adriano Viana Ensinas. "Optimisation for Sustainable Supply Chain of Aviation Fuel, Green Diesel, and Gasoline from Microalgae Cultivated in Sugarcane Vinasse." Processes 13, no. 5 (2025): 1326. https://doi.org/10.3390/pr13051326.

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The development of new technologies for the production of renewable energy is fundamental to reducing greenhouse gas emissions. Therefore, the search for new energy generation methods that are environmentally responsible, socially rational, and economically viable is gaining momentum in order to mitigate carbon footprint. The aviation sector is responsible for a significant fraction of greenhouse gas emissions; for this reason, the decarbonisation of this sector must be investigated using biorefinery models. This study presents a mixed-integer linear programming (MILP) model for optimising the

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Hodencq, Sacha, Mathieu Brugeron, Jaume Fitó, Lou Morriet, Benoit Delinchant, and Frédéric Wurtz. "OMEGAlpes, an Open-Source Optimisation Model Generation Tool to Support Energy Stakeholders at District Scale." Energies 14, no. 18 (2021): 5928. http://dx.doi.org/10.3390/en14185928.

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Energy modelling is key in order to face the challenges of energy transition. There is a wide variety of modelling tools, depending on their purpose or study phase. This article summarises their main characteristics and highlights ones that are relevant when it comes to the preliminary design of energy studies at district scale. It introduces OMEGAlpes, a multi-carrier energy modelling tool to support stakeholders in the preliminary design of district-scale energy systems. OMEGAlpes is a Mixed-Integer Linear Programming (MILP) model generation tool for optimisation. It aims at making energy mo

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35

Laing, Harry, Chris O'Malley, Anthony Browne, Tony Rutherford, Tony Baines, and Mark J. Willis. "Development of a biogas distribution model for a wastewater treatment plant: a mixed integer linear programming approach." Water Science and Technology 82, no. 12 (2020): 2761–75. http://dx.doi.org/10.2166/wst.2020.363.

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Abstract In this paper, we propose a realistic model for gas distribution of an advanced municipal wastewater treatment works and through minimisation of the total cost of gas distribution we perform retrospective optimisation (RO) using historical plant data. This site is the first in the UK with a mixed operational strategy for biomethane produced on site: to burn in combined heat and power (CHP) engines to create electricity, burn in steam boilers for onsite steam use or inject the biomethane into the National Grid. In addition, natural gas can be imported to make up shortfalls in biomethan

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36

Ismail Adeyemi ADEYEMO, Oluwadare Olatunde AKINROGUNDE, Sunday Adeleke SALIMON, and Oluwaseyi Wasiu ADEBIYI. "Adaptive particle swarm optimization approach to simultaneous reconfiguration and shunt capacitor allocation in radial distribution network." Global Journal of Engineering and Technology Advances 12, no. 3 (2022): 077–94. http://dx.doi.org/10.30574/gjeta.2022.12.3.0162.

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Simultaneous radial distribution network reconfiguration (RDNR) and shunt capacitor allocation (SCA) is one of the compensation techniques that are used for getting an improved radial structure with reduced real power loss and enhanced voltage stability. This study presents a novel adaptive particle swarm optimisation (APSO) technique for the simultaneous RDNR and SCA, which is a complex and nonlinear optimisation problem. Unlike the conventional particle swarm optimization (PSO) technique in which an initial population of particles is randomly generated, the fundamental loop concept is used t

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37

Cheng Seong, Khor. "A Model-Based Optimisation Approach for Process Synthesis of Olefins from Petroleum with Application to the Malaysian Petrochemical Industry." ASM Science Journal 12 (December 30, 2019): 1–15. http://dx.doi.org/10.32802/asmscj.2019.393.

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The shale gas revolution has rekindled interest in olefins production due to the abundance of ethane as a raw material resource. However, the main technology still revolves around the cost-intensive distillation operation. Hence this work aims to investigate the economic optimisation of olefins synthesis from petroleum in the light of recent developments. A model-based approach is applied to determine the optimal sequencing of separation and reaction processes for a multi-component hydrocarbon mixture feed to produce mainly ethylene and propylene. a mixed-integer linear program (MILP) is formu

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Ismail, Adeyemi ADEYEMO, Olatunde AKINROGUNDE Oluwadare, Adeleke SALIMON Sunday, and Wasiu ADEBIYI Oluwaseyi. "Adaptive particle swarm optimization approach to simultaneous reconfiguration and shunt capacitor allocation in radial distribution network." Global Journal of Engineering and Technology Advances 12, no. 3 (2022): 077–94. https://doi.org/10.5281/zenodo.7180413.

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Simultaneous radial distribution network reconfiguration (RDNR) and shunt capacitor allocation (SCA) is one of the compensation techniques that are used for getting an improved radial structure with reduced real power loss and enhanced voltage stability. This study presents a novel adaptive particle swarm optimisation (APSO) technique for the simultaneous RDNR and SCA, which is a complex and nonlinear optimisation problem. Unlike the conventional particle swarm optimization (PSO) technique in which an initial population of particles is randomly generated, the fundamental loop concept is used t

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Luo, Jiaxiang, and Jiyin Liu. "An MILP model and clustering heuristics for LED assembly optimisation on high-speed hybrid pick-and-place machines." International Journal of Production Research 52, no. 4 (2013): 1016–31. http://dx.doi.org/10.1080/00207543.2013.828173.

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40

Hadri, Mohamed, Vincenzo Trovato, Agnes Bialecki, Bruno Merk, and Aiden Peakman. "Assessment of High-Electrification UK Scenarios with Varying Levels of Nuclear Power and Associated Post-Fault Behaviour." Energies 14, no. 6 (2021): 1780. http://dx.doi.org/10.3390/en14061780.

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Renewable integration into the electricity system of Great Britain (GB) is causing considerable demand for additional flexibility from plants. In particular, a considerable share of this flexibility may be dispatched to secure post-fault transient frequency dynamics. Pursuant to the unprecedented changes to the traditional portfolio of generation sources, this work presents a detailed analysis of the potential system-level value of unlocking flexibility from nuclear electricity production. A rigorous enhanced mixed integer linear programming (MILP) unit commitment formulation is adopted to sim

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Garcia, Victor Fernandes, Reynaldo Palacios, and Adriano Ensinas. "Optimisation of Ammonia Production and Supply Chain from Sugarcane Ethanol and Biomethane: A Robust Mixed-Integer Linear Programming Approach." Processes 12, no. 10 (2024): 2204. http://dx.doi.org/10.3390/pr12102204.

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Low-carbon ammonia production is crucial for sustainable development. Brazil, a top ethanol producer, can boost competitiveness and cut emissions by integrating ammonia and ethanol production. However, optimal location and production strategy identification is challenging due to existing possibilities and uncertainties. For that, a new MILP superstructure with robust optimisation was developed and used to analyse low-carbon ammonia production integration in the ethanol industry in São Paulo state by ethanol and biomethane routes, in two different scenarios. As for the results, in scenario 1, b

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Luo, Jiaxiang, Jiyin Liu, and Yueming Hu. "An MILP model and a hybrid evolutionary algorithm for integrated operation optimisation of multi-head surface mounting machines in PCB assembly." International Journal of Production Research 55, no. 1 (2016): 145–60. http://dx.doi.org/10.1080/00207543.2016.1200154.

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Chen, Qian Matteo, Alberto Finzi, Toni Mancini, Igor Melatti, and Enrico Tronci. "MILP, Pseudo-Boolean, and OMT Solvers for Optimal Fault-Tolerant Placements of Relay Nodes in Mission Critical Wireless Networks*." Fundamenta Informaticae 174, no. 3-4 (2020): 229–58. http://dx.doi.org/10.3233/fi-2020-1941.

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In critical infrastructures like airports, much care has to be devoted in protecting radio communication networks from external electromagnetic interference. Protection of such mission-critical radio communication networks is usually tackled by exploiting radiogoniometers: at least three suitably deployed radiogoniometers, and a gateway gathering information from them, permit to monitor and localise sources of electromagnetic emissions that are not supposed to be present in the monitored area. Typically, radiogoniometers are connected to the gateway through relay nodes. As a result, some degre

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Erichsen, Gerrit, Tobias Zimmermann, and Alfons Kather. "Effect of Different Interval Lengths in a Rolling Horizon MILP Unit Commitment with Non-Linear Control Model for a Small Energy System." Energies 12, no. 6 (2019): 1003. http://dx.doi.org/10.3390/en12061003.

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In this paper, a fixed electricity producer park of both a short- and long-term renewable energy storage (e.g., battery, power to gas to power) and a conventional power plant is combined with an increasing amount of installed volatile renewable power. For the sake of simplicity, the grid is designed as a single copper plate with island restrictions and constant demand of 1000 MW; the volatile input is deducted from scaled 15-min input data of German grid operators. A mixed integer linear programming model is implemented to generate an optimised unit commitment (UCO) for various scenarios and c

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Sigalo, Marvin B., Saptarshi Das, Ajit C. Pillai, and Mohammad Abusara. "Real-Time Economic Dispatch of CHP Systems with Battery Energy Storage for Behind-the-Meter Applications." Energies 16, no. 3 (2023): 1274. http://dx.doi.org/10.3390/en16031274.

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The use of combined heat and power (CHP) systems has recently increased due to their high combined efficiency and low emissions. Using CHP systems in behind-the-meter applications, however, can introduce some challenges. Firstly, the CHP system must operate in load-following mode to prevent power export to the grid. Secondly, if the load drops below a predefined threshold, the engine will operate at a lower temperature and hence lower efficiency, as the fuel is only half-burnt, creating significant emissions. The aforementioned issues may be solved by combining CHP with a battery energy storag

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Zhao, Xiancong, Hao Bai, Xin Lu, Qi Shi, and Jiehai Han. "A MILP model concerning the optimisation of penalty factors for the short-term distribution of byproduct gases produced in the iron and steel making process." Applied Energy 148 (June 2015): 142–58. http://dx.doi.org/10.1016/j.apenergy.2015.03.046.

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Papaleonidas, Christos, Dimitrios V. Lyridis, Alexios Papakostas, and Dimitris Antonis Konstantinidis. "An innovative decision support tool for liquefied natural gas supply chain planning." Maritime Business Review 5, no. 1 (2020): 121–36. http://dx.doi.org/10.1108/mabr-09-2019-0036.

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Purpose The purpose of this paper is to improve the tactical planning of the stakeholders of the midstream liquefied natural gas (LNG) supply chain, using an optimisation approach. The results can contribute to enhance the proactivity on significant investment decisions. Design/methodology/approach A decision support tool (DST) is proposed to minimise the operational cost of a fleet of vessels. Mixed integer linear programming (MILP) used to perform contract assignment combined with a genetic algorithm solution are the foundations of the DST. The aforementioned methods present a formulation of

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Oliveira, Miguel Castro, Susana M. Vieira, Muriel Iten, and Henrique A. Matos. "Optimisation of Water-Energy Networks in Process Industry: Implementation of Non-Linear and Multi-Objective Models." Frontiers in Chemical Engineering 3 (January 20, 2022). http://dx.doi.org/10.3389/fceng.2021.750411.

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The improvement of water and energy use in the industrial sector is an important concern to improve the overall techno-economic performance of single plants. The most recent EU strategy for energy system integration has been treating these issues in the redaction of its first pillar, which is based on the relations between the promotion of circular economy and energy efficiency and it has as specific objectives the promotion of waste heat recovery and energy recovery from wastewater. Although on the context of research and industrial appliance both waste heat recovery and water recycling and r

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Miguel, Castro Oliveira, M. Vieira Susana, Iten Muriel, and A. Matos Henrique. "Optimisation of Water-Energy Networks in Process Industry: Implementation of Non-Linear and Multi-Objective Models." July 22, 2022. https://doi.org/10.3389/fceng.2021.750411.

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The improvement of water and energy use in the industrial sector is an important concern to improve the overall techno-economic performance of single plants. The most recent EU strategy for energy system integration has been treating these issues in the redaction of its first pillar, which is based on the relations between the promotion of circular economy and energy efficiency and it has as specific objectives the promotion of waste heat recovery and energy recovery from wastewater. Although on the context of research and industrial appliance both waste heat recovery and water recycling and r

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50

Liu, Chao, Yingjie Ma, Dongda Zhang, and Jie Li. "A feasible path-based branch and bound algorithm for strongly nonconvex MINLP problems." Frontiers in Chemical Engineering 4 (September 19, 2022). http://dx.doi.org/10.3389/fceng.2022.983162.

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In this paper, a feasible path-based branch and bound (B&amp;B) algorithm is proposed to solve mixed-integer nonlinear programming problems with highly nonconvex nature through integration of the previously proposed hybrid feasible-path optimisation algorithm and the branch and bound method. The main advantage of this novel algorithm is that our previously proposed hybrid steady-state and time-relaxation-based optimisation algorithm is employed to solve a nonlinear programming (NLP) subproblem at each node during B&amp;B. The solution from a parent node in B&amp;B is used to initia

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