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A Policy-Based Meta-Heuristic Algorithm for Energy-Aware Distributed No-Wait Flow-Shop Scheduling in Heterogeneous Factory Systems

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2025年第1期55卷 620-634页

作者： Zhao, Fuqing Song, Lisi Jiang, Tao Wang, Ling Dong, Chenxin Lanzhou Univ Technol Sch Comp & Commun Lanzhou 730050 Peoples R China Southern Univ Sci & Technol Dept Comp Sci & Engn Shenzhen 518055 Peoples R China Tsinghua Univ Dept Automat Beijing 100084 Peoples R China Qingdao Hengxing Univ Sci & Technol Dept Automot Engn Qingdao 266100 Peoples R China

In the face of environmental deterioration and global climate change, the concept of carbon neutrality and carbon peaking has gained prominence as a means to balance development and environmental preservation worldwide. Energy-aware scheduling is becoming the key scenario for environment conservation in manufacturing. This study focuses on addressing the energy-aware distributed no-wait flow-shop scheduling problem in a heterogeneous factory system (EDNWFSP-HFS) to minimize total energy consumption (TEC) and total tardiness (TTDs). A mixed-integer linear programming (MILP) model is formulated and a policy-based meta-heuristic algorithm (MHA-PG) is specifically designed to solve EDNWFSP-HFS. First, the optimal allocation rules based on random sequence (OAR-RS) are designed to initialize the population. Second, a policy-based method is employed to guide the algorithm toward making a better decision. Third, the energy-saving strategy considering specific knowledge of EDNWFSP-HFS is summarized to further optimize the feasible solution. Extensive simulations are conducted, comparing the performance of MHA-PG against several state-of-the-art algorithms. The results demonstrate that the proposed algorithm outperforms the competing approaches in solving EDNWFSP-HFS, indicating its superior performance and effectiveness.

关键词： Climate change Manufacturing automation Metaheuristics Job shop scheduling Distributed management Energy management Heterogeneous networks Carbon neutral mixed integer linear programming Distributed flow-shop scheduling energy-aware scheduling heterogeneous factory system (HFS) policy-based meta-heuristic

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Hydrogen energy storage train scheduling with renewable generation and demand response

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JOURNAL OF ENERGY STORAGE 2025年 115卷

作者： Gupta, Pranda Prasanta Kalkhambkar, Vaiju Sharma, Kailash Chand Bhui, Pratyasa GLA Univ Dept Elect Engn Mathura Uttar Pradesh India Rajarambapu Inst Technol Dept Elect Engn Sangli Maharashtra India Dr B R Ambedkar Natl Inst Technol Dept Elect & Commun Engn Jalandhar India Indian Inst Technol Dharwad Dept Elect Engn Dharwad India

Large-scale penetration of renewable and hydrogen energy sources represents promising trends toward carbon emission reductions in the power sector. The storage systems such as the hydrogen energy storage (HES) Train will be crucial in responding to extreme grid events due to their agility and flexibility. This manuscript proposes a stochastic network constrained unit commitment (NCUC) considering HES Train with solar PV generation and demand response program (DRP). The DRP is introduced as a flexible option for dealing with energy market prices, providing sustainable options, and modifying the load profile for peak load shaving. The proposed model is applied to manage an HES Train that provides hydrogen energy services with low electricity prices. Moreover, the vector autoregressive moving average (VARMA) model is used in the stochastic optimization strategy to handle uncertain solar PV power. The model is formulated as a mixed integer linear programming (MILP) problem along with a generalized bender decomposition technique (GBD) to obtain the global optimal solution. A sensitivity analysis is presented to analyze solar power's ability to handle the high demand of the system operation. The proposed NCUC problem is simulated using GAMS software on an IEEE 24-bus system. HES Train scheduling with DRP and uncertain solar PV reduces the overall cost by 8.71 % as compared to the thermal-HES Train system.

关键词： Demand response program Hydrogen energy service providers Hydrogen energy storage train Network-constrained unit commitment Solar power generation mixed integer linear programming

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The Exchange Attack and the Mixture Differential Attack Revisited: From the Perspective of Automatic Evaluation

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Chinese Journal of Electronics 2024年第1期33卷 19-29页

作者： Kexin QIAO Zhiyu ZHANG Zhongfeng NIU Liehuang ZHU School of Cyberspace Science and Technology Beijing Institute of Technology State Key Laboratory of Cryptology Institute of Information Engineering Chinese Academy of Sciences School of Cryptography University of Chinese Academy of Sciences

Recent results show that the differential properties within quadruples boom as a new inspiration in cryptanalysis of Advanced Encryption Standard(AES)-like constructions. These methods include the exchange attack proposed in Asiacrypt'19, the mixture differential attack proposed in To SC'18, etc., where the essential properties are obtained by manually scrutinizing the structures of the AES-like constructions. This paper presents a novel framework and an automatic tool based on mixed integer linear programming to search for mixture differential distinguishers for general constructions. This framework considers what equality patterns among quadruples can make a distinguisher and traces how the patterns propagate through cipher components with accurate probability *** this tool, a 5-round AES distinguishing attack with lower complexity and more 6-round distinguishing attacks in the chosen plaintext scenarios are deduced. We prove that no exchange-type or mixture differential distinguisher exists for 7 and above rounds AES if the details of the Sbox and Mix Columns matrix are not taken into account.

关键词： mixed integer linear programming Automatic search Mixture differential cryptanalysis Exchange attack Advanced Encryption Standard (AES)

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Heuristics Based Optimization for Multidepot Drone Location and Routing Problem to Detect Post-Earthquake Damages

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2024年第1期25卷 850-858页

作者： Aydin, Nezir Yilmaz, Oktay Deveci, Muhammet Lv, Zhihan Yildiz Tech Univ Dept Ind Engn TR-34349 Istanbul Turkiye ERD Informat Technol TR-34873 Istanbul Turkiye Imperial Coll London Royal Sch Mines London SW7 2AZ England Natl Def Univ Turkish Naval Acad Dept Ind Engn TR-34940 Istanbul Turkiye Uppsala Univ Fac Arts Dept Game Design S-62167 Visby Sweden

The aim of this research is to detect the post-disaster damage by drones as soon as possible so that decision makers can assign search and rescue teams effectively and efficiently. The main differences of this research from the others, which use drones in literature, are as: First, the regions are divided into grids and different importance values are assigned according to the number of buildings that are likely to be damaged and are vital for the response stage, such as hospitals, schools, and fire stations. Second, these importance levels are updated based on the day and time, which helps ordering the grids in a more realistic manner. Third, the depots are selected among the pre-determined candidate locations in accordance with the purpose of objective function. Fourth, detection times at grids are considered as uncertain. Fifth, two versions of Ant Colony Optimization (ACO) are developed as alternatives to exact solution tools. Last, sensitivity analyzes are performed by reducing the number of sorties, reducing the number of drones, and comparing day and night importance values for each instance. According to the results, only for very small-scale instances, exact solution tool was able to reach the optimal while both versions of ACO reached to similar results within a very less CPU times. Additionally, these ACO algorithms also found good results for the larger scaled problems. Then the performance of these ACO algorithms and the exact solution method are compared based on the CPU time and solution quality.

关键词： Drones Earthquakes Buildings Routing Mathematical models Path planning Image resolution Post-earthquake damage detection location and routing ant colony optimization mixed integer linear programming drones

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Static and Dynamic Routing, Fiber, Modulation Format, and Spectrum Allocation in Hybrid ULL Fiber-SSMF Elastic Optical Networks

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IEEE ACCESS 2025年 13卷 21652-21664页

作者： Ouyang, Kangao Tang, Fengxian Yuan, Zhilin Li, Jun Li, Yongcheng Soochow Univ Sch Elect & Informat Engn Suzhou 215006 Jiangsu Peoples R China Shenzhen Polytech Univ Sch Integrated Circuits Shenzhen 518000 Guangdong Peoples R China

Traditional standard single-mode fibers (SSMFs) are unable to satisfy the future long-distance and high-speed optical channel transmission requirement due to their relatively large signal losses. To address this issue, the ultra-low loss and large effective area (ULL) fibers are successfully manufactured and expected to deployed in the existing optical networks. For such ULL fiber deployment, network operators prefer adding ULL fibers to each link rather than replace existing SSMFs, resulting in a scenario where both of SSMF and ULL fiber coexist on the same link. In this paper, we investigated the routing, fiber, modulation format, and spectrum allocation (RFMSA) problem in the context of an elastic optical network (EON) where ULL fiber and SSMF coexisting on each link under both the static and dynamic traffic demands. We formulated this RFMSA problem as a node-arc based mixed integer linear programming (MILP) model and developed Spectrum Window Plane (SWP)-based heuristic algorithms based on different fiber selection strategies, including spectrum usage based (SU), optical signal-to-noise ratio (OSNR) aware, ULL fiber first (UFF), and random strategies. Simulation results show that in the static traffic demand situation, the RFMSA algorithm based on the OSNR-aware (OA) strategy exhibits optimal performance, attaining a performance similar to that of the MILP model regarding the maximum number of frequency slots (FSs) used in the entire network. Moreover, in the dynamic traffic demand scenario, the SU strategy remarkably surpasses the other strategies in terms of the lightpath blocking probability.

关键词： Optical fiber networks Heuristic algorithms Routing Modulation Signal to noise ratio Resource management Optical noise Elastic optical networks Propagation losses Optical fiber losses ultra-low loss fiber mixed integer linear programming routing fiber modulation format spectrum allocation

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Optimal Allocation and Sizing of Battery Energy Storage System in Distribution Network Using Mountain Gazelle Optimization Algorithm

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ENERGIES 2025年第2期18卷 379-379页

作者： Mumtahina, Umme Alahakoon, Sanath Wolfs, Peter Cent Queensland Univ Sch Engn & Technol Rockhampton Qld 4701 Australia Cent Queensland Univ Sch Engn & Technol Gladstone Qld 4680 Australia

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 the voltage profile and minimize the power loss. During the daily operation of the distribution grid, the charging and discharging behaviour is controlled by minimizing the voltage at each bus. The energy storage dispatch curve along with the locations and sizes are given as inputs to MGO to improve the voltage profile and reduce the line loss. Simulations are carried out in the MATLAB programming environment using an Australian radial distribution feeder, with results showing a reduction in system losses by 8.473%, which outperforms Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), and Cuckoo Search Algorithm (CSA) by 1.059%, 1.144%, and 1.056%, respectively. During the peak solar generation period, MGO manages to contain the voltages within the upper boundary, effectively reducing reverse power flow and enhancing voltage regulation. The voltage profile is also improved, with MGO achieving a 0.348% improvement in voltage during peak load periods, compared to improvements of 0.221%, 0.105%, and 0.253% by GWO, WOA, and CSA, respectively. Furthermore, MGO's optimization achieves a reduction in the fitness value to 47.260 after 47 iterations, demonstrating faster and more consistent convergence compared to GWO (47.302 after 60 iterations), WOA (47.322 after 20 iterations), and CSA (47.352 after 79 iterations). This comparative analysis highlights the effectiveness of

关键词： battery energy storage system line loss reduction mixed integer linear programming mountain gazelle optimization algorithm radial distribution network voltage profile improvement

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A decision support system for optimised industrial water management

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EXPERT SYSTEMS WITH APPLICATIONS 2025年 271卷

作者： Vatikiotis, Stavros Avgerinos, Ioannis Plitsos, Stathis Zois, Georgios Athens Univ Econ & Business Dept Management Sci & Technol 76 Patis Ave Athens 10434 Greece Univ Piraeus Dept Ind Management & Technol 80 Karaoli & Dimitriou str Piraeus 18534 Greece

Water scarcity and the low quality of wastewater produced in industrial applications present significant challenges, particularly in managing fresh water intake and reusing residual quantities. These issues affect various industries, compelling plant owners and managers to optimise water resources within their process networks. To address this cross-sector business requirement, we propose a Decision Support System (DSS) designed to capture key network components, such as inlet streams, processes, and outlet streams. Data provided to the DSS are exploited by an optimisation module, which supports both network design and operational decisions. This module is coupled with a generic mixed-integer nonlinear programming (MINLP) model, which is linearised into a compact mixed-integer linear programming (MILP) formulation capable of delivering fast optimal solutions across various network designs and input parameterisations. Additionally, a Constraint programming (CP) approach is incorporated to handle nonlinear expressions through straightforward modelling. This state-ofthe-art generalised framework enables broad applicability across a wide range of real-world scenarios, setting it apart from the conventional reliance on customised solutions designed for specific use cases. The proposed framework was tested on 500 synthetic data instances inspired by historical data from three case studies. The obtained results confirm the validity, computational competence and practical impact of our approach both among their operational and network design phases, demonstrating significant improvements over current practices. Notably, the proposed approach achieved a 17.6% reduction in freshwater intake in a chemical industry case and facilitated the reuse of nearly 90% of wastewater in an oil refinery case.

关键词： Network flow optimisation mixed integer linear programming Freshwater minimisation Wastewater reuse Process network design User Requirements Analysis

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New models for the cryptanalysis of ASCON

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DESIGNS CODES AND CRYPTOGRAPHY 2025年 1-18页

作者： Degre, Mathieu Derbez, Patrick Lahaye, Lucie Schrottenloher, Andre Univ Rennes Inria CNRS IRISA Rennes France ENS Lyon Lyon France

This paper focuses on the cryptanalysis of the ASCON family using automatic tools. We analyze two different problems with the goal to obtain new modelings, both simpler and less computationally heavy than previous works (all our models require only a small amount of code and run on regular desktop computers). The first problem is the search for Meet-in-the-middle attacks on reduced-round ASCON-XOF. Starting from the MILP modeling of Qin et al. (Meet-in-the-middle preimage attacks on sponge-based hashing. In: EUROCRYPT (4). Lecture notes in computer science, vol 14007. Springer, pp. 158-188, 2023. https://***/10.1007/978-3-031-30634-1_6), we rephrase the problem in SAT, which accelerates significantly the solving time and removes the need for the "weak diffusion structure" heuristic. This allows us to reduce the memory complexity of Qin et al.'s attacks and to prove some optimality results. The second problem is the search for lower bounds on the probability of differential characteristics for the ASCON permutation. We introduce a lossy MILP encoding of the propagation rules based on the Hamming weight, in order to find quickly lower bounds which are comparable to the state of the art. We find a small improvement over the existing bound on 7 rounds.

关键词： ASCON Symmetric Cryptanalysis Meet-in-the-middle Attacks Differential Cryptanalysis mixed integer linear programming SAT

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Deterministic Multistage Constellation Reconfiguration Using integer programming and Sequential Decision-Making Methods

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JOURNAL OF SPACECRAFT AND ROCKETS 2024年第1期62卷 206-222页

作者： Lee, Hang Woon Rogers, David O. Williams Pearl, Brycen D. Chen, Hao Ho, Koki West Virginia Univ Dept Mech Mat & Aerosp Engn Morgantown WV 26506 USA Stevens Inst Technol Sch Syst & Enterprises Hoboken NJ 07030 USA Georgia Inst Technol Daniel Guggenheim Sch Aerosp Engn Atlanta 30332 GA USA

This paper addresses the problem of reconfiguring Earth observation satellite constellation systems through multiple stages. The Multistage Constellation Reconfiguration Problem (MCRP) aims to maximize the total observation rewards obtained by covering a set of targets of interest through the active manipulation of the orbits and relative phasing of constituent satellites. This paper considers deterministic problem settings in which the targets of interest are known a priori. We propose a novel integer linear programming formulation for MCRP, capable of obtaining provably optimal solutions. To overcome computational intractability due to the combinatorial explosion in solving large-scale instances, we introduce two computationally efficient sequential decision-making methods based on the principles of a myopic policy and a rolling horizon procedure. The computational experiments demonstrate that the devised sequential decision-making approaches yield high-quality solutions with improved computational efficiency over the baseline MCRP. Finally, a case study using Hurricane Harvey data showcases the advantages of multistage constellation reconfiguration over single-stage and no-reconfiguration scenarios.

关键词： Satellite Constellations Satellite Maneuvers Remote Sensing and Applications Mathematical Optimization Orbit Design mixed integer linear programming Earth Observation Astrodynamics Space Systems Operations Research

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Runway assignment optimisation model for Istanbul Airport considering multiple parallel runway operations

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AERONAUTICAL JOURNAL 2024年第1330期128卷 2799-2814页

作者： Guven, A. Cetek, F. Aybek Cecen, R. K. Gen Directorate State Airports Author DHMI Ankara Turkiye Eskisehir Tech Univ Eskisehir Turkiye Eskisehir Osmangazi Univ Eskisehir Turkiye

The aviation industry has rapidly developed in recent years. Due to the increased number of flight operations, managing air traffic has become essential. The air traffic management system aims to reduce the air traffic control workload and use existing resources more efficiently. This study proposed a new mixed integer linear programming model to minimise the total fuel consumption during taxi operations for the runway assignment problem, comparing the actual Istanbul Airport runway assignment data. The average taxi times are calculated using the 30,000-flight operations data for each arrival and departure taxi route. Also, 47 different aircraft types are obtained using the data for the fuel consumption calculation. The International Civil. Aviation Organisation (IACO) aircraft engine emissions databank provides the fuel consumption values for each aircraft according to engine type. This approach allows our model to calculate more realistic fuel consumption for taxi operations, as each aircraft engine type has a different fuel consumption value. The proposed model is implemented at Istanbul Airport, the busiest airport in Turkey, where multiple parallel runway operations are applied. The results showed that the proposed model reduced total fuel consumption for taxi operations between 6.6% and 14.4% compared to the actual Istanbul Airport runway assignment data.

关键词： runway assignment optimisation multiple parallel runways taxi operation mixed integer linear programming air traffic management

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