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The green capacitated lot sizing for industrial symbiosis

Transportation Research Procedia 2025年 84卷 610-617页

作者： Khalid Saad Albadia Ibrahim Adebola Kazeem Mohammad A.M. Abdel-Aal Industrial & Systems Engineering Department King Fahd University of Petroleum and Minerals Dhahran 31261 Saudi Arabia Interdisciplinary Research Center of Smart Mobility & Logistics King Fahd University of Petroleum and Minerals Dhahran 31261 Saudi Arabia

Given the detrimental effects that climate change is having on the ecosystems and general health of our world, we must all work to mitigate or prevent it. Cutting back on carbon emissions is one method we can use to mitigate the effects of climate change. At levels that nature is unable to balance on its own, manufacturing has been a major contributor to the dramatic rise in carbon emissions. In this context, a green capacitated lot-sizing problem in the structure of an industrial symbiosis (GCLS-IS), where two production units (PU1 and PU2) must plan their production over a planning horizon of T periods was considered. PU1 must limit its emissions to a certain government approved CO2 quota in a production period t to satisfy a deterministic time-dependent demand. In this paper, carbon emission is assumed to be proportional to the number of units produced per period and can be expressed as a unitary environmental impact. Two types of carbon emission constraints were studied: periodic carbon emission constraints and cumulative carbon emission constraints. Valuable insights derived from this analysis are subsequently used to discuss the managerial implications of setting up the considered industrial symbiosis in terms of model complexity. The periodic and cumulative cases are proven to be NP-hard. Three models were developed; (i) without carbon emissions (ii) periodic carbon emissions (iii) cumulative carbon emission. Upon solving the models with pyomo, model 3 was found to be better than model 2 since it had a lower cost, lower inventory, lower disposal quantity, and did not exceed the approved carbon emissions. Additionally, perspectives to extend this work are discussed.

关键词： Green capacitated lot sizing problem Industrial symbiosis Waste management Periodic carbon emissions Cumulative carbon emissions mixed integer linear programming

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Mathematical programming-Based Design Structure Matrix Clustering for Optimal Modular Architecture Design

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Journal of Mechanical Design 2025年第10期147卷 101401页

作者： Kim, Jaewoo Choi, Euihyeon Ahn, Jaemyung Suh, Eun Suk Kim, Jeong-Hoon Lim, Dong Gyu Department of Aerospace Engineering Korea Advanced Institute of Science and Technology (KAIST) 291 Daehak-ro Yuseong-Gu Daejeon 34141 South Korea https://***/01zkghx44Georgia Institute of Technology North Avenue Atlanta GA 30332 Graduate School of Engineering Practice Seoul National University 1 Gwanak-ro Gwanak-gu Seoul 08826 South Korea Vehicle Architecture Module Planning Team Hyundai Motor Company 150 Hyundaiyeonguso-ro Hwaseong Gyeonggi-do 18280 South Korea

This article introduces a new mixed integer linear programming (MILP) approach to the modular architecture design problem based on the design structure matrix (DSM). The DSM modularization (clustering) problem aims to maximize the modularity (quantified by the Q-metric) under constraints reflecting practical design/manufacturing/maintenance considerations. A MILP formulation is developed to optimize a modular architecture under constraints. The developed formulation is verified through two case studies on the subsystems of an automobile and an electric train. Both case studies successfully demonstrate the proposed formulation's effectiveness, highlighting its practical applicability.

关键词： design optimization design structure matrix mixed integer linear programming Design systems engineering multi-objective optimization design for X modular architecture design decision theory constrained clustering

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Optimal linear power flow for droop controlled islanded microgrid

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2024年 160卷

作者： Uniyal, Ankit Sarangi, Saumendra Rawat, Mahiraj Singh DIT Univ Dept Elect & Elect & Commun Engn Dehra Dun 248009 Uttarakhand India Natl Inst Technol Uttarakhand Dept Elect Engn Pauri Garhwal 246174 Uttarakhand India Motilal Nehru Natl Inst Technol Allahabad Dept Elect Engn Prayagraj 211004 UP India

The time of optimal planning and operation of islanded microgrid (IMG) can be minimized by modeling it as non -iterative mixed integer linear problem (MILP). In this respect, conventional non-linear power flow model needs to be transformed to its linearized form without loss of accuracy and robustness. In the present work, a linearized droop based power flow model for IMG has been developed which takes the advantage of topology of the network by modeling it in form of matrices to reduce computation time and complexity. The proposed method is compared to earlier developed non-linear power flow models for IMG. Further, linear power flow equations are formulated as MILP for optimal dump load allocation problem to resolve V and f fluctuations in an IMG. The results of proposed MILP formulation are compared with another proposed MINLP based non -iterative method and an already existing MINLP based iterative method which involves non-linear power flow and heuristic techniques. The IEEE 33 -node and 69 -node radial distribution networks (DNs) have been modified as droop controlled IMGs and used as test beds. The work has been conducted in GAMS/MATLAB.

关键词： Distributed generation Dump load mixed integer linear programming Microgrid planning Optimization Power flow

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Day-ahead operation of a multi-energy microgrid community with shared hybrid energy storage and EV integration

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JOURNAL OF ENERGY STORAGE 2024年 97卷

作者： Khan, Muhammad Ahsan Rehman, Talha Hussain, Akhtar Kim, Hak-Man Incheon Natl Univ Dept Elect Engn 119 Acad Ro Incheon 22012 South Korea Laval Univ Dept Elect & Comp Engn Quebec City PQ Canada Incheon Natl Univ Res Inst Northeast Asian Super Grid 119 Acad Ro Incheon 22012 South Korea

Seasonal variations in demand and renewable generation present challenges for investing in fixed storage systems due to high costs and reduced adaptability, especially for multi-energy microgrids (MEMGs) that cater to diverse demand dimensions. To address these issues, this study presents a collaborative model of the MEMG community comprising electric, thermal, cooling, and an emerging hydrogen network with shared hybrid energy storage (SHES). The SHES comprises of electric storage, a heat storage tank, and a hydrogen storage system to serve multiple demands within MEMGs. To this end, a day-ahead mixed integer linear programming (MILP)-based model is developed with internal multi-energy trading to minimize the overall costs and emissions of the MEMG community. Additionally, the dynamic capacity allocation strategy of SHES is adopted to address variations in demand and renewable. Electric vehicles (EVs) providing vehicle-to-grid (V2G) services are also incorporated, and Monte Carlo simulations (MCS) are performed to address uncertainties. The results show that the proposed model effectively reduces the cost and emissions of the MEMG community by 0.6% and 1.9% compared with individual storage structures. The comparative analysis with conventional SHES architecture (ESS+HSS and ESS+TSS) shows the economic feasibility of the proposed model with a cost reduction of 0.8% and 0.7%. Additionally, the consideration of multi-energy trading reduces the cost and emissions by 0.59% and 5.3%. Thus, the proposed model proves to be both economically and environmentally viable.

关键词： Capacity allocation Electric vehicle Energy trading Multi-energy microgrid mixed integer linear programming Shared hybrid energy storage

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The multi-fleet delivery problem combined with trucks, tricycles, and drones for last-mile logistics efficiency requirements under multiple budget constraints

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2024年 187卷

作者： Chen, Enming Zhou, Zhongbao Li, Ruiyang Chang, Zhongxiang Shi, Jianmai Hunan Univ Sch Business Adm Changsha 410082 Peoples R China Changsha Univ Sci & Technol Sch Traff & Transport Engn Changsha 410114 Peoples R China Natl Univ Def Technol Coll Syst Engn Changsha 410073 Peoples R China

In the increasingly competitive urban logistics delivery business field, enhancing last-mile logistics efficiency with constrained budgets is crucial for logistics companies. With the increasing adoption of emerging vehicles in last-mile logistics, neglecting the capacity of traditional vehicles may be uneconomical. This paper introduces the multi-fleet delivery problem combined with Trucks, Tricycles, and Drones (MFDP-TTD) for last-mile logistics efficiency requirements under multiple budget constraints, which represents a novel variant of the Two-Echelon Vehicle Routing Problem. Compared to the truck-drone mode, truck-tricycle mode, and the Two-Echelon Vehicle Routing Problem, by adding the collaboration of an emerging delivery vehicle (drones) and a traditional delivery vehicle (tricycle), the MFDP-TTD improves the speed of delivery of last-mile logistics more cost-efficiently. To tackle this intricate issue, this paper devises a mixed integer linear programming (MILP) model, taking into account fixed cost-related budgets and operating cost-related budgets. The model allows for the integration of diverse numbers of tricycles and drones across various fleets, with larger vehicles accommodating smaller ones to moving. In addition, some valid inequalities based on the properties of the problem are presented to accelerate the solution process. To solve this problem efficiently on a large scale, the paper proposes a multi-start improved adaptive large neighborhood search algorithm (MS-IALNS) that combines the advantages of an adaptive large neighborhood search algorithm and an ant colony algorithm. In addition, four fast feasibility-checking strategies designed based on valid inequalities are proposed. Extensive computational experiments demonstrate the validity of the MILP model and valid inequalities and the advantages of the MS-IALNS. Compared to the multi-fleet delivery problem with Trucks and Tricycles, the Two-Echelon Vehicle Routing Problem, the two-echelon cit

关键词： Last-mile logistics Heterogeneous-vehicle collaboration Multiple budget constraints mixed integer linear programming Adaptive large neighborhood search algorithm

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Scheduling Landing and Payload Switch of Unmanned Aerial Vehicles on a Single Automatic Platform 18

Scheduling Landing and Payload Switch of Unmanned Aerial Veh...

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IEEE 18th International Conference on Automation Science and Engineering (IEEE CASE)

作者： Ausonio, Elena Bagnerini, Patrizia Gaggero, Mauro Univ Genoa Genoa Italy Natl Res Council Italy Genoa Italy

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

We focus on the problem of optimally managing a set of unmanned aerial vehicles performing given missions that require to land on an automatic platform, unmount the currently-carried payload, and take off with another payload to complete mission objectives. Such a problem often arises when swarms of drones cooperate to complete monitoring applications or other tasks requiring an efficient schedule of landings and payload switches in a resource-constrained environment. First, the problem is formulated as a mixed-integer linear programming one, which, however, may be complex to be solved for a large number of drones. Thus, we also propose a heuristic algorithm able to find suboptimal solutions with a reduced computational effort. Preliminary simulation results are reported and discussed.

关键词： Schedules Processor scheduling Simulation Autonomous aerial vehicles Real-time systems mixed integer linear programming Task analysis

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Distributed Optimization for mixed-integer Consensus in Multi-Agent Networks

Distributed Optimization for Mixed-Integer Consensus in Mult...

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European Control Conference (ECC)

作者： Liu, Zonglin Stursberg, Olaf Univ Kassel EECS Control & Syst Theory Kassel Germany

ISBN: (数字)9783907144077

ISBN: (纸本)9783907144077

This paper considers the consensus of mixed-integer linear programming (MILP) problems as occurring in distributed control and machine learning of multi-agent networks. Unlike existing work on consensus problems, in which the agents only have to agree on the continuous part of their decision variables, this paper proposes a new method to enable them to also agree on the integer part. This mixed-integer setting may arise from distributed control problems of hybrid dynamical systems, or distributed machine learning problems using support vector machines. It is shown in this paper that the consensus of mixed-integer variables is guaranteed to be achieved by a tailored series of continuous consensus problems.

关键词： Support vector machines Decentralized control Europe Machine learning programming mixed integer linear programming Dynamical systems

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Enhancing target benefits of power system stakeholders: A columns and constraint generation-based power-to-gas linked economic dispatch

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ELECTRIC POWER SYSTEMS RESEARCH 2024年 229卷

作者： Son, Yeong-Geon Kwak, Joosik Park, Seong-Jun Kim, Sung-Yul Keimyung Univ Daegu South Korea Korea Elect Power Res Inst Daejeon South Korea

Economic dispatch (ED) plays a crucial role in optimizing power plant output to minimize the cost of electricity production and ensure economic efficiency in complex power systems. However, with the growing emphasis on carbon neutrality policies and the increased use of renewable energy sources (RES), traditional ED models may lead to economic losses for independent power producers (IPP) and renewable energy providers (REP). To address this challenge, a new ED model is proposed in this study, which integrates power-to-gas (P2G) technology and takes into account the perspectives of all stakeholders, including independent system operator (ISO) IPP, and REP. The proposed approach is tested in the context of the cost based pool (CBP) market structure in S. Korea, where a mixed integer linear programming (MILP) problem is solved for each target benefit using columns and constraint generations (C&CG). By ensuring the target benefits of each stakeholder group, this improved ED model aims to encourage their participation in the power system and support economic efficiency. The simulation results of the P2G-linked ED proposed in this paper verify that as the capacity of the integrated P2G increases, there is an increase in the improvement rate of each target benefit for ISO, IPP, and REP.

关键词： Economic dispatch Power to Gas Columns and constraint generations mixed integer linear programming Two -stage Taylor Series

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Virtualized network functions resource allocation in network functions virtualization using mathematical programming

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COMPUTER COMMUNICATIONS 2024年 228卷

作者： Moradi, Mahsa Ahmadi, Mahmood PourKarimi, Latif Razi Univ Comp Engn & Informat Technol Dept Kermanshah Iran Razi Univ Dept Math Kermanshah Iran

Network Functions Virtualization (NFV) revolutionizes network services by eliminating the need for dedicated hardware. This virtualization enables flexible and efficient deployment of various network functions like proxies, firewalls, and load balancers. Providing the service requested by the user in the network is done by a sequence of virtual network functions, which are known as service functions chain. One of the main challenges in the development of network functions virtualization architecture is the allocation of resources to the requested network services in network infrastructures, this challenge is called network function virtualization resource allocation problem. Therefore, this paper addresses the resource allocation problem in Network Functions Virtualization (NFV) architectures using mathematical programming techniques. A multi-objective mixed-integer linear programming (MILP) model is proposed to optimize resource allocation for virtual network functions (VNFs). The model incorporates constraints related to node and link resource capacities, as well as delay requirements. The objective functions focus on maximizing network throughput, minimizing node resource costs (CPU cores and memory), reducing capital and operational expenses, and ensuring efficient execution time. These constraints and objective functions are formally defined by mathematical functions. The proposed mathematical model is implemented and solved using the Cplex solver. To evaluate the effectiveness of the proposed mathematical model, various network topologies were evaluated under different parameters. These parameters included the length of Service Function Chains (SFCs), the number and length of flows, node resource capacities, the number of nodes and VNFs. The experimental results demonstrated the model's ability to efficiently allocate resources to VNFs across these different scenarios.

关键词： Network functions virtualization architecture Virtualized network functions Resource allocation Mathematical programming mixed integer linear programming

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A novel parallel heuristic method to design a sustainable medical waste management system

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JOURNAL OF CLEANER PRODUCTION 2024年 452卷

作者： Amirteimoori, Arash Tirkolaee, Erfan Babaee Amirteimoori, Alireza Khakbaz, Amir Simic, Vladimir London Sch Econ & Polit Sci LSE Dept Math Columbia HouseHoughton St London WC2A 2AE England Istinye Univ Dept Ind Engn TR-34396 Istanbul Turkiye Yuan Ze Univ Dept Ind Engn & Management Taoyuan Taiwan Middle East Univ MEU Res Unit Amman Jordan Istinye Univ Fac Engn & Nat Sci Dept Biomed Engn TR-34396 Istanbul Turkiye Damghan Univ Sch Engn Dept Ind Engn Damghan Iran Univ Belgrade Fac Transport & Traff Engn Vojvode Stepe 305 Belgrade 11010 Serbia Korea Univ Coll Informat Dept Comp Sci & Engn Seoul 02841 South Korea

Efficient management of waste generated in healthcare systems is crucial to minimize its environmental impact and ensure public health. Sustainable medical waste management (MWM) systems require careful network design, which can be achieved through efficient optimization techniques. This work develops a mixed -integer linear programming (MILP) to formulate the problem, a two-step MILP (TSMILP) to generate quality lower bounds, and a novel parallel heuristic algorithm to configure a sustainable waste management system including waste generation centers (WGCs), waste treatment centers (WTCs), waste recycling centers (WRCs), waste disposal centers (WDCs) and waste incineration centers (WICs). Such a hybrid methodology has not been yet offered in the literature wherein the aim is to address strategic (establishment of facilities), tactical (employment of transportation system), and operational decisions (transportation planning) optimally in large networks. As reflected in the literature, there is a huge gap in efficiency and application of combinatorial optimization, and parallel computing in sustainable MWM systems, where the suggested MILPs ' solvers are not technically capable of discovering quality solutions in reasonable runtimes on large -sized instances. Thus, we suggest a novel heuristic equipped with parallel computing to share the complexity of the problem, with all the CPU cores to shorten runtime. Comparing the results generated by the parallel heuristic with those of the sequential heuristic, the MILP, and the TSMILP on three sets of benchmark instances using Nemenyi ' s post -hoc procedure for Friedman ' s test, it is inferred that the parallel heuristic is so effective in coping with the problem, and produces high -quality solutions, especially on the large -sized set. Finally, sensitivity analysis is adopted to analyze the effects of parameters on the objective values and provide useful managerial insights.

关键词： Supply chain management Medical waste management Parallel computing Heuristic Sustainable development mixed integer linear programming

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