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Journal articles on the topic 'Bi-objective dispatch problem'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

Meziane, Mohammed Amine, Youssef Mouloudi, and Abdelghani Draoui. "Comparative study of the price penalty factors approaches for Bi-objective dispatch problem via PSO." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 4 (2020): 3343. http://dx.doi.org/10.11591/ijece.v10i4.pp3343-3349.

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One of the main objectives of electricity dispatch centers is to schedule the operation of available generating units to meet the required load demand at minimum operating cost with minimum emission level caused by fossil-based power plants. Finding the right balance between the fuel cost the green gasemissionsis reffered as Combined Economic and Emission Dispatch (CEED) problem which is one of the important optimization problems related the operationmodern power systems. The Particle Swarm Optimization algorithm (PSO) is a stochastic optimization technique which is inspired from the social le

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Mohammed, Amine Meziane, Mouloudi Youssef, and Draoui Abdelghani. "Comparative study of the price penalty factors approaches for Bi-objective dispatch problem via PSO." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 4 (2020): 3343–49. https://doi.org/10.11591/ijece.v10i4.pp3343-3349.

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One of the main objectives of electricity dispatch centers is to schedule the operation of available generating units to meet the required load demand at minimum operating cost with minimum emission level caused by fossil-based power plants. Finding the right balance between the fuel cost the green gasemissionsis reffered as Combined Economic and Emission Dispatch (CEED) problem which is one of the important optimization problems related the operationmodern power systems. The Particle Swarm Optimization algorithm (PSO) is a stochastic optimization technique which is inspired from the social le

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3

Hu, Fei Hu, Ji Ze Zhang, Bei Long Ma, and Lu Lu Liu. "Bi-Objective Power Dispatch on Micro-Grid System Using Improved Genetic Algorithms." Advanced Materials Research 614-615 (December 2012): 1738–43. http://dx.doi.org/10.4028/www.scientific.net/amr.614-615.1738.

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In this paper, a micro-grid power dispatch network is built up, and a real-number-coded genetic algorithm is adapted and proposed to solve the bi-objective dispatch problem, which is to minimize both fuel cost and production cost simultaneously. By using hybrid factors, we turn the two objectives into a single one, and then solve it by the improved genetic algorithm. Test results show the efficiency of the proposed algorithm.

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Tran, Cuong Dinh, Thang Trung Nguyen, Hanh Minh Hoang, and Bao Quoc Nguyen. "One Rank Cuckoo Search Algorithm for Bi-Objective Load Dispatch Problem." International Journal of Grid and Distributed Computing 9, no. 4 (2016): 13–26. http://dx.doi.org/10.14257/ijgdc.2016.9.4.02.

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Dekhici, Latifa, Khaled Guerraiche, and Khaled Belkadi. "Environmental Economic Power Dispatch Using Bat Algorithm with Generalized Fly and Evolutionary Boundary Constraint Handling Scheme." International Journal of Applied Metaheuristic Computing 11, no. 2 (2020): 171–91. http://dx.doi.org/10.4018/ijamc.2020040109.

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This article intends to resolve the evolving environmental economic power dispatching problem (EED) using an enhanced version of the bat algorithm (BA) which is the Bat Algorithm with Generalized Fly (BAG). A good solution based on the Evolutionary Boundary Constraint Handling Scheme rather than the well-known absorbing technique and a good choice of the bi-objective function are provided to maintain the advantages of such algorithms on this problem. In the first stage, an individual economic power dispatch problem is considered by minimizing the fuel cost and taking into account the maximum p

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Dridi, Tawba, Houda Jouini, Abdelkader Mami, Abderrahman El Mhamedi, and El Mouloudi Dafaoui. "Application of the Slime Mould Algorithm on the Bi-Objective Environmental Economic Dispatch Problem." Engineering, Technology & Applied Science Research 13, no. 6 (2023): 12190–97. http://dx.doi.org/10.48084/etasr.6358.

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This paper investigates the performance of one of the latest metaheuristic swarm-based approaches called Slime Mould Algorithm (SMA). SMA is used here to solve the static bi-objective constrained Economic Emission Dispatch (EED) problem in the presence of renewable energy sources while considering the Valve-Point Effects (VPE). The SMA approach is applied to indicate the adequate optimal solutions for operating the committed thermal units under different operational constraints. The sought optimal solutions are the midpoint between cost saving and pollutant gas emission reduction. This study a

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Panigrahi, B. K., Manjaree Pandit, Hari Mohan Dubey, Ashish Agarwal, and Wei-Chiang Hong. "Invasive Weed Optimization for Combined Economic and Emission Dispatch Problems." International Journal of Applied Evolutionary Computation 5, no. 1 (2014): 1–18. http://dx.doi.org/10.4018/ijaec.2014010101.

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In this paper, Invasive Weed Optimization (IWO) algorithm is used to find the optimum solution of Combined Economic Emission Dispatch (CEED) problem. The main objective is to minimize the fuel cost as well as emission level, while satisfying the power demand and associative operational constraints. The bi-objective problem is made to a single objective function using the price penalty factor. Since, the minimize fuel cost and emission are contradictory to each other so to get the optimum compromise solution, weighing factor is used. IWO is applied on three different standard test cases i.e. 6

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Azizivahed, Ali, Ali Arefi, Ehsan Naderi, Hossein Narimani, Mehdi Fathi, and Mohammad Rasoul Narimani. "An Efficient Hybrid Approach to Solve Bi-objective Multi-area Dynamic Economic Emission Dispatch Problem." Electric Power Components and Systems 48, no. 4-5 (2020): 485–500. http://dx.doi.org/10.1080/15325008.2020.1793830.

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9

Tsai, Ming Tang. "The Operation Dispatch of Cogeneration Systems in the Deregulation Environment." Applied Mechanics and Materials 590 (June 2014): 516–20. http://dx.doi.org/10.4028/www.scientific.net/amm.590.516.

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In this paper, an optimal strategy was presented to solve the operation dispatch of cogeneration systems in a deregulated market. With the load demand including steam and electricity, the operational model of cogeneration system was derived by considering the bi-lateral contracts and operation constraints. The objective function is formulated the profit-maximizing problem in the searching process. Sequential Quadratic Programming (SQP) was used to solve this problem. Test results verify that SQP can offer an efficient way for cogeneration plants to meet the load growth and promoted the compete

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Zhang, Jiahui, Zhiyu Xu, Weisheng Xu, Feiyu Zhu, Xiaoyu Lyu, and Min Fu. "Bi-Objective Dispatch of Multi-Energy Virtual Power Plant: Deep-Learning-Based Prediction and Particle Swarm Optimization." Applied Sciences 9, no. 2 (2019): 292. http://dx.doi.org/10.3390/app9020292.

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This paper addresses the coordinative operation problem of multi-energy virtual power plant (ME-VPP) in the context of energy internet. A bi-objective dispatch model is established to optimize the performance of ME-VPP in terms of economic cost (EC) and power quality (PQ). Various realistic factors are considered, which include environmental governance, transmission ratings, output limits, etc. Long short-term memory (LSTM), a deep learning method, is applied to the promotion of the accuracy of wind prediction. An improved multi-objective particle swarm optimization (MOPSO) is utilized as the

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Feng, Lim Yuan, Nor Azwan Mohamed Kamari, Ahmad Asrul Ibrahim, Syahirah Abd Halim, Mohd Asyraf Zulkifley, and Muhamad Zahim Sujod. "Search and Rescue Optimization for Combined Economic Load and Emission Dispatch." Jurnal Kejuruteraan 36, no. 2 (2024): 801–9. http://dx.doi.org/10.17576/jkukm-2024-36(2)-37.

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The goal of combined economic and emission dispatch (CEED) in the power system is to solve the economics management of generators in order to achieve both minimum fuel prices and pollution levels while meeting load demands and operating limits. The Search and Rescue (SAR) optimization methodology is developed in this study to address the CEED problem, and the results gained are compared with the Evolutionary Programming and Flower Pollination Algorithm methods. Those analyses are able to evaluate the effectiveness as well as the rate of convergence of the methods under consideration. In genera

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Hakimifar, Mohammadmehdi, Vera C. Hemmelmayr, and Fabien Tricoire. "A Bi-Objective Field-Visit Planning Problem for Rapid Needs Assessment under Travel-Time Uncertainty." Sustainability 14, no. 5 (2022): 3024. http://dx.doi.org/10.3390/su14053024.

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After a sudden-onset disaster strikes, relief agencies usually dispatch assessment teams to the affected region to quickly investigate the impacts of the disaster on the affected communities. Within this process, assessment teams should compromise between the two conflicting objectives of a “faster” assessment, which covers the needs of fewer community groups, and a “better” assessment, i.e., covering more community groups over a longer time. Moreover, due to the possible effect of the disaster on the transportation network, assessment teams need to make their field-visit planning decisions un

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Guo, Linze. "Optimal Solution Design for Initial Post-earthquake Casualty Dispatch Considering Road Disruption Scenarios: Based on Network Optimization Model." Highlights in Science, Engineering and Technology 35 (April 11, 2023): 77–89. http://dx.doi.org/10.54097/hset.v35i.7035.

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The optimization of casualty dispatch is a key problem faced in the initial post-earthquake relief process. In view of the urgency and uncertainty of casualty rescue in the early post-earthquake period, this paper investigates the decision optimization problem of casualty dispatching in the early post-earthquake period. Based on the fact that current research on emergency disaster relief in the early post-earthquake period rarely considers the bi-objective optimization problem of transport time and system cost, this paper quantifies the risk of road disruption based on the earthquake risk leve

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14

Basetti, Vedik, Shriram S. Rangarajan, Chandan Kumar Shiva, et al. "Economic Emission Load Dispatch Problem with Valve-Point Loading Using a Novel Quasi-Oppositional-Based Political Optimizer." Electronics 10, no. 21 (2021): 2596. http://dx.doi.org/10.3390/electronics10212596.

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In the present paper, a novel meta-heuristic algorithm, namely quasi-oppositional search-based political optimizer (QOPO), is proposed to solve a non-convex single and bi-objective economic and emission load dispatch problem (EELDP). In the proposed QOPO technique, an opposite estimate candidate solution is performed simultaneously on each candidate solution of the political optimizer to find a better solution of EELDP. In the bi-objective EELDP, QOPSO is applied to simultaneously minimize fuel costs and emissions by considering various constraints such as the valve-point loading effect (VPLE)

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Nagarajan, Karthik, Ayalur Krishnamoorthy Parvathy, and Arul Rajagopalan. "Multi-Objective Optimal Reactive Power Dispatch using Levy Interior Search Algorithm." International Journal on Electrical Engineering and Informatics 12, no. 3 (2020): 547–70. http://dx.doi.org/10.15676/ijeei.2020.12.3.8.

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In planning and operation processes of power systems, the most critical and outstanding problem is the optimal scheduling of reactive power resources. The current research study considered real power loss as well as the deviation of voltage magnitude as objective functions since these two play important roles in a power system’s operations and control. Due to the above-mentioned considerations, bi-objective optimization takes a form here. In the recent times, lot of meta-heuristic optimization techniques was implemented to elucidate ORPD problem. One such recently advanced algorithm named Inte

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Jing, Xiuyan, Liantao Ji, and Huan Xie. "Bi-Level Inverse Robust Optimization Dispatch of Wind Power and Pumped Storage Hydropower Complementary Systems." Processes 12, no. 4 (2024): 729. http://dx.doi.org/10.3390/pr12040729.

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This paper presents a bi-level inverse robust economic dispatch optimization model consisting of wind turbines and pumped storage hydropower (PSH). The inner level model aims to minimize the total generation cost, while the outer level introduces the optimal inverse robust index (OIRI) for wind power output based on the ideal perturbation constraints of the objective function. The OIRI represents the maximum distance by which decision variables in the non-dominated frontier can be perturbed. Compared to traditional methods for quantifying the worst-case sensitivity region using polygons and el

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Yajure Ramírez, César Aristóteles. "Resolution of the bi-objective optimization problem for the dispatch of hydroelectric plants under conditions of low inflow using the NSGA II algorithm." Revista Tecnológica - ESPOL 36, no. 1 (2024): 32–43. http://dx.doi.org/10.37815/rte.v36n1.1146.

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Among the consequences of climate change are increased temperatures and changes in rainfall patterns that bring longer periods of drought. This creates limitations in the administration of hydroelectric plant reservoirs, restricting, in some cases, the amount of electrical energy generated. The objective of this research is to solve the multi-objective optimization problem that seeks to minimize the production of electrical energy from hydroelectric plants with low inflow and, at the same time, minimize electrical rationing due to this low production. As these objectives conflict with each oth

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18

Lin, Hongji, Chongyu Wang, Fushuan Wen, et al. "Risk-Limiting Real-Time Economic Dispatch in a Power System with Flexibility Resources." Energies 12, no. 16 (2019): 3133. http://dx.doi.org/10.3390/en12163133.

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The integration of numerous intermittent renewable energy sources (IRESs) poses challenges to the power supply-demand balance due to the inherent intermittent and uncertain power outputs of IRESs, which requires higher operational flexibility of the power system. The deployment of flexible ramping products (FRPs) provides a new alternative to accommodate the high penetration of IRESs. Given this background, a bi-level risk-limiting real-time unit commitment/real-time economic dispatch model considering FRPs provided by different flexibility resources is proposed. In the proposed model, the obj

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19

Kadali, Kalyan Sagar, Moorthy Veeraswamy, Marimuthu Ponnusamy, and Viswanatha Rao Jawalkar. "Linear interpolated multi-objective economic emission scheduling using grey wolf optimizer: a strategic balance and solution with diverse load pattern." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 41, no. 1 (2021): 427–54. http://dx.doi.org/10.1108/compel-01-2021-0022.

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Purpose The purpose of this paper is to focus on the cost-effective and environmentally sustainable operation of thermal power systems to allocate optimum active power generation resultant for a feasible solution in diverse load patterns using the grey wolf optimization (GWO) algorithm. Design/methodology/approach The economic dispatch problem is formulated as a bi-objective optimization subjected to several operational and practical constraints. A normalized price penalty factor approach is used to convert these objectives into a single one. The GWO algorithm is adopted as an optimization too

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20

Aydın, Nadi Serhan. "A seismic-risk-based bi-objective stochastic optimization framework for the pre-disaster allocation of earthquake search and rescue units." Mathematical Modelling and Numerical Simulation with Applications 4, no. 3 (2024): 370–94. http://dx.doi.org/10.53391/mmnsa.1517843.

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Accurately predicting earthquakes' time, location and size is nearly impossible with today’s technology. Severe earthquakes require prompt and effective mobilization of available resources, as the speed of intervention has a direct impact on the number of people rescued alive. This, in turn, calls for a strategic pre-disaster allocation of search and rescue (SAR) units, both teams and equipment, to make the deployment of resources as quick and equitable as possible. In this paper, a seismic risk-based framework is introduced that takes into account distance-based contingencies between cities.

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Mumtahina, Umme, Sanath Alahakoon, and Peter Wolfs. "Optimal Allocation and Sizing of Battery Energy Storage System in Distribution Network Using Mountain Gazelle Optimization Algorithm." Energies 18, no. 2 (2025): 379. https://doi.org/10.3390/en18020379.

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This paper addresses the problem of finding the optimal position and sizing of battery energy storage (BES) devices using a two-stage optimization technique. The primary stage uses mixed integer linear programming (MILP) to find the optimal positions along with their sizes. In the secondary stage, a relatively new algorithm called mountain gazelle optimizer (MGO) is implemented to find the technical feasibility of the solution, such as voltage regulation, energy loss reduction, etc., provided by the primary stage. The main objective of the proposed bi-level optimization technique is to improve

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22

Clawson, Jeff, Christopher Olola, Andy Heward, Brett Patterson, and Greg Scott. "Profile of Emergency Medical Dispatch Calls for Breathing Problems within the Medical Priority Dispatch System Protocol." Prehospital and Disaster Medicine 23, no. 5 (2008): 412–19. http://dx.doi.org/10.1017/s1049023x00006142.

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AbstractIntroduction:A common chief complaint to emergency dispatch communication centers worldwide is “breathing problems”. The chief complaint of breathing problems represents a wide spectrum of underlying diseases, patient conditions, and onset types. The current debate is on the potential ability of a dispatch protocol to safely and with high specificity, differentiate patients with minor or non-critical conditions from those conditions that pose risk to the patient and require advanced life support evaluation and care. This issue also has extended into the paramedic prehospital evaluation

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Joe, Waldy, Hoong Chuin Lau, and Jonathan Pan. "Reinforcement Learning Approach to Solve Dynamic Bi-objective Police Patrol Dispatching and Rescheduling Problem." Proceedings of the International Conference on Automated Planning and Scheduling 32 (June 13, 2022): 453–61. http://dx.doi.org/10.1609/icaps.v32i1.19831.

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Police patrol aims to fulfill two main objectives namely to project presence and to respond to incidents in a timely manner. Incidents happen dynamically and can disrupt the initially-planned patrol schedules. The key decisions to be made will be which patrol agent to be dispatched to respond to an incident and subsequently how to adapt the patrol schedules in response to such dynamically-occurring incidents whilst still fulfilling both objectives; which sometimes can be conflicting. In this paper, we define this real-world problem as a Dynamic Bi-Objective Police Patrol Dispatching and Resche

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Wang, Yongjia, Hao Zhong, Xun Li, Wenzhuo Hu, and Zhenhui Ouyang. "Optimal Configuration of Distributed Pumped Storage Capacity with Clean Energy." Energies 18, no. 15 (2025): 3896. https://doi.org/10.3390/en18153896.

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Aiming at the economic problems of industrial users with wind power, photovoltaic, and small hydropower resources in clean energy consumption and trading with superior power grids, this paper proposes a distributed pumped storage capacity optimization configuration method considering clean energy systems. First, considering the maximization of the investment benefit of distributed pumped storage as the upper goal, a configuration scheme of the installed capacity is formulated. Second, under the two-part electricity price mechanism, combined with the basin hydraulic coupling relationship model,

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Niknamfar, Amir Hossein, Seyed Armin Akhavan Niaki, and Marziyeh karimi. "A series-parallel inventory-redundancy green allocation system using a max-min approach via the interior point method." Assembly Automation 38, no. 3 (2018): 323–35. http://dx.doi.org/10.1108/aa-07-2017-085.

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Purpose The purpose of this study is to develop a novel and practical series-parallel inventory-redundancy allocation system in a green supply chain including a single manufacturer and multiple retailers operating in several positions without any conflict of interests. The manufacturer first produces multi-product and then dispatches them to the retailers at different wholesale prices based on a common replenishment cycle policy. In contrast, the retailers sell the purchased products to customers at different retail prices. In this way, the manufacturer encounters a redundancy allocation probl

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Tiwari, Gourav, and Devendra Dohare. "A Review Paper on Economic Load Dispatch Problem." International Journal of Advanced Research in Science, Communication and Technology, February 1, 2021, 1–7. http://dx.doi.org/10.48175/ijarsct-747.

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Efficient methods for solving economic load dispatch (ELD) problems have been provided to build effective multi-objective evolutionary algorithms (MOEAs). ELD is a dynamic bi-objective optimization problem that is strictly limited. The MOEA applications to solve the ELD problems have been published in various publications since the 1990s. This paper explores the state of the art of this direction-related research. It addresses subjects such as standard MOEAs, traditional ELD problems, dynamic ELD problems, wind power integration ELD problems, electric car integration ELD problems and micro-gri

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Gholami, Khalil, Maysam Abbasi, Ali Azizivahed, and Li Li. "An efficient bi-objective approach for dynamic economic emission dispatch of renewable-integrated microgrids." Journal of Ambient Intelligence and Humanized Computing, August 6, 2022. http://dx.doi.org/10.1007/s12652-022-04343-5.

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AbstractTo overcome the challenges of conventional power systems, such as increasing power demand, requirements of stability and reliability, and increasing integration of renewable energy sources, the concept of microgrids was introduced and is currently one of the most important solutions for solving the mentioned problems. Generally, microgrids have two operating modes, namely grid-connected and islanded modes. Based on the literature and its unique characteristics, the islanded mode is more challenging than the other one. In this paper, a new self-adaptive comprehensive differential evolut

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Sahoo, Arun Kumar, Tapas Kumar Panigrahi, Soumya Ranjan Das, and Aurobinda Behera. "Chaotic butterfly optimization algorithm applied to Multi objective Economic and Emission dispatch in modern power system." Recent Advances in Computer Science and Communications 13 (August 18, 2020). http://dx.doi.org/10.2174/2666255813999200818140528.

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Aims : To optimize the economic and emission dispatch of the thermal power plant. Background: Considering both the economic and environmental aspects, a combined approach had made to attain a solution is known as the combined economic and emission dispatch problem. The CEED problem is a nonlinear bi-objective problem with conflicting behaviour with all the practical constraints. Objective: A new optimization method is improvised by applying the chaotic mapping to the butterfly optimization algorithm. This method is applied to the Combined Economic and Emission Dispatch (CEED) problem for optim

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Ravandi, Fatemeh, Azar Fathi Heli Abadi, Ali Heidari, Mohammad Khalilzadeh, and Dragan Pamucar. "A bi-objective model for location, dispatch and relocation of ambulances with a revision of dispatch policies." Kybernetes, April 23, 2024. http://dx.doi.org/10.1108/k-11-2023-2491.

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PurposeUntimely responses to emergency situations in urban areas contribute to a rising mortality rate and impact society's primary capital. The efficient dispatch and relocation of ambulances pose operational and momentary challenges, necessitating an optimal policy based on the system's real-time status. While previous studies have addressed these concerns, limited attention has been given to the optimal allocation of technicians to respond to emergency situation and minimize overall system costs.Design/methodology/approachIn this paper, a bi-objective mathematical model is proposed to maxim

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Ali, Aamir, Sumbal Aslam, Sohrab Mirsaeidi, et al. "Multi‐objective multiperiod stable environmental economic power dispatch considering probabilistic wind and solar PV generation." IET Renewable Power Generation, August 27, 2024. http://dx.doi.org/10.1049/rpg2.13077.

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AbstractThe economic‐environmental power dispatch (EEPD) problem, a widely studied bi‐objective non‐linear optimization challenge in power systems, traditionally focuses on the economic dispatch of thermal generators without considering network security constraints. However, environmental sustainability necessitates reducing emissions and increasing the penetration of renewable energy sources (RES) into the electrical grid. The integration of high levels of RES, such as wind and solar PV, introduces stability issues due to their uncertain and intermittent nature. This article addresses these c

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Ming-Tang, Tsai, and Yen Chih-Wei. "Interactive Compromise Approach with Particle Swarm Optimization for Environmental/Economic Power Dispatch." August 22, 2009. https://doi.org/10.5281/zenodo.1057841.

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In this paper, an Interactive Compromise Approach with Particle Swarm Optimization(ICA-PSO) is presented to solve the Economic Emission Dispatch(EED) problem. The cost function and emission function are modeled as the nonsmooth functions, respectively. The bi-objective including both the minimization of cost and emission is formulated in this paper. ICA-PSO is proposed to solve EED problem for finding a better compromise solution. The solution methodology can offer a global or near-global solution for decision-making requirements. The effectiveness and efficiency of ICA-PSO are demonstrated by

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Zhang, Zongnan, Jun Du, Menghan Li, Jing Guo, Zhenyang Xu, and Weikang Li. "Bi-Level Optimization Dispatch of Integrated-Energy Systems With P2G and Carbon Capture." Frontiers in Energy Research 9 (January 12, 2022). http://dx.doi.org/10.3389/fenrg.2021.784703.

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The power-to-gas (P2G) technology transforms the unidirectional coupling of power network and natural gas network into bidirectional coupling, and its operational characteristics provide an effective way for wind and solar energy accommodation. The paper proposes a bi-level optimal dispatch model for the integrated energy system with carbon capture system and P2G facility. The upper model is an optimal allocation model for coal-fired units, and the lower model is an economic dispatch model for the integrated energy system. Moreover, the upper model is solved by transforming the model into a mi

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Sakthivel, V. Ponnuvel, and P. Duraisamy Sathya. "Fuzzified Coulomb’s and Franklin’s laws behaved optimization for economic dispatch in multi-area multi-fuel power system." SN Applied Sciences 3, no. 1 (2021). http://dx.doi.org/10.1007/s42452-020-04017-x.

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AbstractMulti-Area Multi-Fuel Economic Dispatch (MAMFED) aims to allocate the best generation schedule in each area and to offer the best power transfers between different areas by minimizing the objective functions among the available fuel alternatives for each unit while satisfying various constraints in power systems. In this paper, Fuzzified Coulomb’s and Franklin’s Laws Behaved Optimization (FCFLBO) approach is proposed to solve the MAMFED problem. Coulomb’s and Franklin’s Laws Behaved Optimization (CFLBO) approach is developed from Coulomb’s and Franklin’s theories, which encompass fasci

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Sakthivel, V. Ponnuvel, and P. Duraisamy Sathya. "Single and multi-area multi-fuel economic dispatch using a fuzzified squirrel search algorithm." Protection and Control of Modern Power Systems 6, no. 1 (2021). http://dx.doi.org/10.1186/s41601-021-00188-w.

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AbstractMulti-Area Multi-Fuel Economic Dispatch (MAMFED) aims to allocate the best generation schedule in each area and to offer the best power transfers between different areas by minimizing the objective functions among the available fuel alternatives for each unit while satisfying various constraints in power systems. In this paper, a Fuzzified Squirrel Search Algorithm (FSSA) algorithm is proposed to solve the single-area multi-fuel economic dispatch (SAMFED) and MAMFED problems. Squirrel Search Algorithm (SSA) mimics the foraging behavior of squirrels based on the dynamic jumping and glid

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Yin, Yunqiang, Dongwei Li, Dujuan Wang, Yugang Yu, and T. C. E. Cheng. "Truck‐Drone Pickup and Delivery Service Optimization With Availability Profiles." Naval Research Logistics (NRL), December 11, 2024. https://doi.org/10.1002/nav.22238.

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ABSTRACTThe absence of customers at the time of a pickup or delivery service not only results in additional costs associated with the failed service attempt but also decreases customer satisfaction. Thus, it is crucial to account for the possible convenient times of customers when designing the pickup and delivery service scheme. With the advantages of the drone in delivery speed and transport costs, we investigate the truck‐drone pickup and delivery problem with availability profiles, in which each node has an availability profile that consists of a set of service time windows, each of which

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