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An intelligent resource allocation strategy with slicing and auction for private edge cloud systems

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2024年 160卷 879-889页

作者： Peng, Yuhuai Wang, Jing Ye, Xiongang Khan, Fazlullah Bashir, Ali Kashif Alshawi, Bandar Liu, Lei Omar, Marwan Northeastern Univ Sch Comp Sci & Engn Shenyang 110819 Peoples R China Univ Nottingham Ningbo China Fac Sci & Engn Sch Comp Sci Ningbo 315104 Zhejiang Peoples R China Manchester Metropolitan Univ Dept Comp Networks & Cybersecur Manchester England Lebanese Amer Univ Dept Comp Sci & Math Beirut Lebanon Woxsen Univ Woxsen Sch Business Hyderabad 502345 India Umm Al Qura Univ Coll Comp Dept Comp & Network Engn Mecca Saudi Arabia Xidian Univ Guangzhou Inst Technol Guangzhou 510555 Peoples R China IIT Informat Technol & Management Chicago IL USA

The convergence of transformative technologies, including the Internet of Things (IoT), Big Data, and Artificial Intelligence (AI), has driven private edge cloud systems to the forefront of research efforts. The access to massive terminals and the emergence of personalized services pose serious challenges for efficient resource management in power private edge cloud systems. To address the challenge of inequitable resource allocation in the private edge cloud, this work proposes an intelligent resource allocation strategy with a slicing and auction approach. By formalizing the resource allocation problem as a mixed integer nonlinear programming (MINLP) puzzle, the method transforms it into a hierarchical allocation challenge for Mobile Network Operators (MNOs), Mobile Virtual Network Operators (MVNOs), and power terminals. The proposed Multi-hop Progressive Auction Algorithm (MPAA) addresses the sliced resource allocation problem between MNOs and MVNOs. Furthermore, a Terminal Resource Allocation Strategy (TRAS) based on improved particle swarm optimization is proposed to solve the spectrum resource allocation problem between MVNOs and power terminals. Extensive simulation results show that the bidding overhead of MPAA is reduced by 6.12% and the average terminal satisfaction of TRAS is improved by about 1.3% compared to conventional methods, thus improving the utilization of wireless resources within the power AIoT.

关键词： Private edge cloud systems Resource allocation Spectrum slicing Hierarchical auction mixed integer nonlinear programming

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A MINP model and hybrid heuristic algorithm for railway cold chain service network design problem: a case study of China

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2025年第1期63卷 171-192页

作者： Li, Dandan Gan, Mi Qiao, Yu Ou, Qichen Liu, Xiaobo Southwest Jiaotong Univ Sch Transportat & Logist Chengdu Peoples R China Southwest Jiaotong Univ Natl Engn Lab Integrated Transportat Big Data Appl Chengdu Peoples R China Southwest Jiaotong Univ 111 Erhuanlu Beiyiduan Chengdu 610031 Sichuan Peoples R China

Railway Cold Chain Service Network Design (RCC-SND) aims to optimise resource allocation and utilisation to ensure the efficient transportation of perishable foods. In this study, we propose a mixed integer nonlinear programming (MINP) model to solve the hub selection, service frequency determination, wagon flow organisation and routing problems in RCC-SND. The application of the model is illustrated using the real network comprising 163 cities in China. The PSO-GA algorithm is proven effective in solving the problem. Furthermore, we introduce two future scenarios to assess the carbon reduction potential and economic costs of railway cold chain operations. There are some main findings: as the hub number increases from 30 to 40, the total cost decreases, as the hub continues to rise, this reduction is offset by the increased hub operational costs. Increasing hubs can enhance direct train frequency while causing railway capacity redundancy, this redundancy can be addressed by freight volume increase, as demonstrated in this study, 4.5 times increase in freight volume can boost train utilisation by up to 12.5%. By 2030, railway cold chain carbon emissions are projected to exceed 1.1 million tons, the adoption of hydrogen as alternative energy is an economically viable solution for emission reduction.

关键词： Perishable food industry railway cold chain transportation hub-routing problem mixed integer nonlinear programming SDG 9: Industry innovation and infrastructure

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A QoE and Availability-Aware Framework for Network Slice Placement and Resource Allocation

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IEEE ACCESS 2025年 13卷 1481-1495页

作者： Dobreff, Gergely Bader, Attila Pasic, Alija Budapest Univ Technol & Econ Fac Elect Engn & Informat Dept Telecommun & Artificial Intelligence H-1111 Budapest Hungary Ericsson Hungary H-1117 Budapest Hungary

In 5G networks, the deployment of network slices enabled by Software-Defined Networking (SDN) is becoming a critical component for delivering tailored services to meet diverse application needs. However, this introduces challenges in network management, particularly in efficiently allocating resources to ensure that each network slice meets its specific Quality of Service (QoS) and availability requirements. Simultaneously, it must optimize overall network performance and network operator's profit, which is linked to the Quality of Experience (QoE) of the end-users. Existing works offer either an availability-based solution or a QoE-aware solution to this problem, but not both. This paper addresses the end-to-end network slice resource allocation problem by simultaneously considering QoS and availability requirements in slice placement, while employing a QoE-aware strategy for resource allocation. We propose a framework that optimizes the network operator profit i.e. the highest QoE with the least resource usage, and can be flexibly configured to model realistic scenarios. Arbitrary network slice requirements can be defined using slice-specific QoS/QoE mapping, resource requirements, end-to-end latency and availability. For solving the formulated problem a mixed integer nonlinear programming (MINLP) formulation and efficient heuristic methods are proposed. Our solution accounts for the non-linear QoS/QoE relationship, utilizes redundantly placed Service Function Chains (SFCs) to increase availability, and supports the sharing of Virtual Network Functions (VNFs) among SFCs to optimize resource usage. Through extensive simulations on realistic network topologies and slice requests, we demonstrate the framework's effectiveness in offering flexible and efficient network slice placement and resource allocation, utilizing a baseline heuristic from related studies. The results indicate that while the exact method delivers an optimal solution, heuristic approaches are suita

关键词： Quality of experience Resource management Quality of service Substrates Telecommunication network reliability Network slicing Virtual links Measurement Bandwidth Telecommunications Availability mixed integer nonlinear programming E2E network slicing placement quality of experience (QoE) quality of service (QoS) resource allocation service function chaining (SFC)

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MODELLING AND A HYBRID GENETIC ALGORITHM FOR THE EQUITY-ORIENTED WORKER ASSIGNMENT PROBLEM IN SERU PRODUCTION SYSTEMS

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JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION 2024年第1期20卷 36-58页

作者： Wu, Yinghui Zeng, Shaoyu Yu, Yang Jiangsu Univ Sci & Technol Sch Econ & Management Zhenjiang 212100 Peoples R China Northeastern Univ Inst Intelligent Data & Syst Engn State Key Lab Synthet Automat Proc Ind Shenyang 110819 Peoples R China

. Worker assignment is critical for developing a flexible and humancentered seru production system (SPS). Most studies in the literature focus on worker assignment with the objective of maximizing system efficiency, which causes an inescapable consequence that workers with high proficiency levels experience overwork compared with workers with lower proficiency levels. From the perspective of workload equity, we investigate the worker assignment problem in SPS, where the heterogeneity of workers with diverse skill sets and skill proficiency levels is taken into account. A mixed integer nonlinear programming model named the equity-oriented model is proposed for this problem to mitigate the workload inequity among workers by minimizing the maximum workload of workers. The equity-oriented model is linearized and solved by the CPLEX solver for small-scale instances. For efficiently solving large-scale instances, we design a hybrid genetic algorithm combined with local search. Computational experiments demonstrate the high performance of the hybrid genetic algorithm, both in terms of computing time and solution quality. We find that using the equity-oriented model can significantly balance the workload among workers at the cost of minimal increases in the total labor hours.

关键词： Key words and phrases seru Production system worker assignment mixed integer nonlinear programming hybrid genetic algorithm

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A branch-and-price approach for the continuous multifacility monotone ordered median problem

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2023年第1期306卷 105-126页

作者： Blanco, Victor Gazquez, Ricardo Ponce, Diego Puerto, Justo Univ Granada Inst Math IMAG Granada Spain Univ Granada Dept Quant Methods Econ & Business Granada Spain Univ Seville Inst Math IMUS Seville Spain Univ Seville Dept Stats & OR Seville Spain

In this paper, we address the Continuous Multifacility Monotone Ordered Median Problem. The goal of this problem is to locate p facilities in Rd minimizing a monotone ordered weighted median function of the distances between given demand points and its closest facility. We propose a new branch-and -price procedure for this problem, and three families of matheuristics based on: solving heuristically the pricer problem, aggregating the demand points, and discretizing the decision space. We give detailed discussions of the validity of the exact formulations and also specify the implementation details of all the solution procedures. Besides, we assess their performances in an extensive computational experience that shows the superiority of the branch-and-price approach over the compact formulation in medium-sized instances. To handle larger instances it is advisable to resort to the matheuristics that also report rather good results.(c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license ( http://***/licenses/by/4.0/ )

关键词： Combinatorial optimization Continuous location Ordered median problems mixed integer nonlinear programming Branch-and-price

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Multi-venue location optimization with overlapping audience reach areas

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OPERATIONAL RESEARCH 2024年第4期24卷 65页

作者： Shams-Shoaaee, Shervin Dept Natl Def 60 Moodie Dr Ottawa ON K1A 0K2 Canada

The Canadian Armed Forces (CAF) is currently facing recruitment challenges. Similar to target market advertising in other industries, military recruitment can be optimized by aiming recruitment efforts at populations with high enrolment success potential. Using historical data, geographical regions with high potential for recruitment can be identified. This can be used to optimize the reach of recruitment events to high potential geographical regions. This paper looks at applications of facility location optimization in recruitment attraction event planning activities where there are intersections in regions each venue can attract audiences from (venue reach areas), and the probability that the events will attract targeted audience varies by geographical location. This study models the problem as a mixed integer nonlinear problem (MINLP) and provides an exact solution method. This is followed by a case study applying the model to the CAF's recruitment events for a sample geographical area of the Canadian National Capital Region (NCR).

关键词： Military recruitment optimization Facilities' location selection optimization mixed integer nonlinear programming Linear integer programming Discrete optimization

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Joint optimization of electric bus charging and energy storage system scheduling

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Frontiers of Engineering Management 2024年第4期11卷 676-696页

作者： Lingshu ZHONG Ziling ZENG Zikang HUANG Xiaowei SHI Yiming BIE School of Systems Science and Engineering Sun Yat-Sen UniversityGuangzhou 510399China Department of Architecture and Civil Engineering Chalmers University of TechnologyGothenburg SE-41296Sweden School of Civil Engineering and Transportation South China University of TechnologyGuangzhou 510641China Department of Civil and Environmental Engineering University of Wisconsin-MilwaukeeMilwaukeeWI 53211United States School of Transportation Jilin UniversityChangchun 130012China

The widespread use of energy storage systems in electric bus transit centers presents new opportunities and challenges for bus charging and transit center energy management.A unified optimization model is proposed to jointly optimize the bus charging plan and energy storage system power *** model optimizes overall costs by considering battery aging,time-of-use tariffs,and capacity service *** model is linearized by a series of relaxations of the nonlinear *** means that we can obtain the exact solution of the model quickly with a commercial solver that is fully adapted to the time scale of day-ahead *** numerical simulations demonstrate that the proposed method can optimize the bus charging time,charging power,and power profile of energy storage systems in *** Carlo simulations reveal that the proposed method significantly reduces the cost and has sufficient robustness to uncertain fluctuations in photovoltaics and office loads.

关键词： electric vehicle energy storage mixed integer nonlinear programming Monte Carlo simulations public transit

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A MINLP model for the layout design of subsea oil gathering- transportation system in deep water oil field considering avoidance of subsea obstacles and pipe intersections

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OCEAN ENGINEERING 2023年第1期277卷

作者： Hong, Cheng Wang, Yuxi Estefen, Segen F. Ningbo Univ Fac Maritime & Transportat Ningbo 315211 Peoples R China Univ Fed Rio de Janeiro Ocean Engn Dept COPPE BR-21941972 Rio De Janeiro Brazil State key Lab Petr Pollut Control Beijing 102206 Peoples R China CNPC Res Inst Safety & Environm Technol Beijing 102206 Peoples R China

This paper focuses on the layout design of subsea oil gathering-transportation system in deep water oil field. In such a system, subsea manifolds are applied to gather and transport the produced fluids from subsea wells to floating processing terminals. A mixed integer nonlinear programming (MINLP) model is proposed, constrained by a series of operation and production requirements, aiming to minimize the total layout cost. Through the model, the pipe line network topology structure which reflects the allocations among the subsea wells, manifolds and processing terminals, the routes of pipes, as well as the size of the facilities could all be figured out. Two key contributions are made through this work. First, avoiding pipe intersections and subsea obstacles are integrated simultaneously, making the proposed model closer to practical situations. Second, a decomposition strategy based on Delaunay triangulation and gradient descent is constructed, achieving high quality initial solution and stable iteration process. The results of case studies indicate the validity, feasibility and stability of the proposed model and the solution method. Besides, the effect of manifold numbers on the layout optimization result is analyzed through the model, indicating its flexibility in the layout design analysis.

关键词： Subsea oil gathering-transportation Layout design mixed integer nonlinear programming Delaunay triangulation Gradient descent algorithm

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A novel deep reinforcement learning based business model arrangement for Korean net-zero residential micro-grid considering whole stakeholders' interests

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ISA TRANSACTIONS 2023年 137卷 471-491页

作者： Tightiz, Lilia Yoo, Joon Gachon Univ Sch Comp 1342 Seongnam Daero Seongnam 13120 Gyeonggi Do South Korea

In this paper, we put forward a deep reinforcement learning (DRL) based energy management system (EMS) solution for a typical Korean net-zero residential micro-grid (NZR-MG). We model NZR-MG EMS to extract a profitable business model that respects whole stakeholders' interests and meets Korean power system regulations and specifications. We deployed the value-based DRL technique, dual deep Q-learning (DDQN), as a solution for our EMS problem since of its simplicity, stability in the learning process, and non-dependency on hyper-parameter selection compared to actor-critic methods. Due to the implementation of mixed-integer nonlinear programming (MINLP) to solve the reward function in this paper, DDQN, despite other DRL methods, provides precise, explicit, and meaningful rewards. In addition to encouraging the agent to choose profitable actions, this approach releases the proposed DRL-based method from the hindrance of redesigning the reward function experimentally in any future extension of the environment elements. Moreover, attaching transfer learning (TL) to the process of training DDQN agent defeat the MINLP imposed latency in training convergence. An extensive benchmark is proposed to test the superiority of the proposed method versus other DRL algorithms.& COPY;2022 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： Business model Deep reinforcement learning Demand response Energy management system mixed integer nonlinear programming Net -zero building

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Derivative-free mixed binary necklace optimization for cyclic-symmetry optimal design problems

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OPTIMIZATION AND ENGINEERING 2023年第1期24卷 353-394页

作者： Tran, Thi Thoi Sinoquet, Delphine Da Veiga, Sebastien Mongeau, Marcel IFP Energies Nouvelles Rueil Malmaison France Safran Tech Magny Les Hameaux France ENAC Toulouse France

This paper presents an adapted trust-region method for computationally expensive black-box optimization problems with mixed binary variables that involve a cyclic symmetry property. mixed binary problems occur in several practical optimal design problems, e.g., aircraft engine turbines, mooring lines of offshore wind turbines, electric engine stators and rotors. The motivating application for this study is the optimal design of helicopter bladed disk turbomachines. The necklace concept is introduced to deal with the cyclic symmetry property, and to avoid costly black-box objective-function evaluations at equivalent solutions. An adapted distance is proposed for the discrete-space exploration step of the optimization method. A convergence analysis is presented for the trust-region derivative-free algorithm, DFOb-d(H), extended to the mixed-binary case and based on the Hamming distance. The convergence proof is extended to the new algorithm, DFOb-d(neck), which is based on the necklace distance. Computational comparison with state-of-the-art black-box optimization methods is performed on a set of analytical problems and on a simplified industrial application.

关键词： mixed integer nonlinear programming Black-box simulation Derivative-free optimization Trust-region method Cyclic symmetry Necklace distance

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