计算机科学最新文献

{"title":"A decimal artificial bee colony with elite strategy for the cutting stock problem with irregular items","authors":"Qiang Luo ,&nbsp;Chunrong Pan ,&nbsp;Hong Zhong ,&nbsp;Yunqing Rao","doi":"10.1016/j.swevo.2025.102026","DOIUrl":"10.1016/j.swevo.2025.102026","url":null,"abstract":"<div><div>This study investigates an irregular cutting stock problem in various industrial applications, including shipbuilding, construction machinery, and automobiles, where a considerable quantity of metal sheets are consumed. The problem involves cutting the single-size stocks to produce a set of demanded items such that the material utilization is maximized, i.e., the waste is minimized. To address the problem, this study employs the double scanline to represent the irregular items, and proposes a decimal artificial bee colony with elite strategy. The algorithm represents solutions with decimal vectors and uses a decoder procedure to map these vectors to solutions of the problem. In addition, a metaheuristic-based hybrid algorithm is developed for further improving the solution quality. To comprehensively assess the performance of the algorithm, two sets of computational tests were conducted. The experimental results demonstrated that the proposed algorithm outperforms competing algorithms by achieving faster convergence than other metaheuristics of the same class and producing better solutions, verifying the algorithm's effectiveness and superiority. The implementation of the algorithm benefits waste reduction for companies in practice.</div></div>","PeriodicalId":48682,"journal":{"name":"Swarm and Evolutionary Computation","volume":"97 ","pages":"Article 102026"},"PeriodicalIF":8.2,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144534427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An adaptive hybrid neighborhood search algorithm for the electric vehicle pickup and delivery problem with time windows and partial charging","authors":"Saiqi Zhou ,&nbsp;Dezhi Zhang ,&nbsp;Shiyan Fang ,&nbsp;Shuangyan Li","doi":"10.1016/j.swevo.2025.102042","DOIUrl":"10.1016/j.swevo.2025.102042","url":null,"abstract":"<div><div>Environmental pressures and measures are compelling the extensive integration of electric vehicles into transportation and logistics systems. This paper focuses on addressing the electric vehicle pickup and delivery problem with time windows and partial charging, in which the amount of charging electricity at charging stations is flexible and determined based on the route schedules. A new effective mixed-integer linear programming model has been developed for the problem. To effectively tackle large-scale instances, we propose an adaptive hybrid neighborhood search algorithm, which is based on the framework of the adaptive large neighborhood search algorithm. The proposed algorithm incorporates various problem-oriented search operators being adaptively chosen for evolution. Meanwhile, dynamic programming-based charging approaches for both full and partial charging policies are presented. Numerical experiments are conducted using benchmark instances of the electric vehicle pickup and delivery problem to verify the effectiveness of our algorithm configurations and its overall performance. The solution results are compared against those obtained using the state-of-the-art algorithm, and the proposed algorithm identifies 21 new best solutions and exhibits greater stability, which demonstrates the competitiveness of the proposed algorithm. Furthermore, the analysis of charging policies provides interesting insights, highlighting the significant advantage of the partial charging policy in scenarios characterized by clustered customer distributions or short scheduling horizons.</div></div>","PeriodicalId":48682,"journal":{"name":"Swarm and Evolutionary Computation","volume":"97 ","pages":"Article 102042"},"PeriodicalIF":8.2,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144534428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A ranked filter-based three-way clustering strategy for intrusion detection in highly secure IoT networks","authors":"Fazal Wahab ,&nbsp;Shengjun Ma ,&nbsp;Xuze Liu ,&nbsp;Yuhai Zhao ,&nbsp;Anwar Shah ,&nbsp;Bahar Ali","doi":"10.1016/j.compeleceng.2025.110514","DOIUrl":"10.1016/j.compeleceng.2025.110514","url":null,"abstract":"<div><div>The primary issue with the current intrusion detection systems (IDS) for IoT networks is that they are based on two-way decisions, meaning that a decision must be taken regardless of the quality of the information available. This can result in inaccurate classification decisions when there is insufficient and incomplete information. Misclassifying objects can have serious consequences, especially in security-sensitive systems. Moreover, many of these approaches fail to deliver transparent and understandable results from the model, making it difficult to interpret how decisions are being made. To address these limitations, this article proposes a novel ranked filter-based three-way clustering (RF3WC) strategy for intrusion detection, which involves making decisions about acceptance, rejection, or deferment. The inclusion of the deferred decision option allows for the deferment of a specific decision in cases when sufficient information is lacking. Based on a three-way decision, this approach divides the data into three regions: malicious, non-malicious, and suspicious. The inclusion of the suspicious region can make the IDS extremely secure, more reliable, and quite confident and can significantly reduce false alerts. In addition, we employed the eXplainable Artificial Intelligence (XAI) technique to facilitate a more transparent understanding of the model’s output. Results obtained from extensive experiments using four cutting-edge datasets demonstrate that the proposed RF3WC model enhances detection accuracy and minimizes misclassification.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"127 ","pages":"Article 110514"},"PeriodicalIF":4.0,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144535040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Continuous-time successive convexification for constrained trajectory optimization","authors":"Purnanand Elango ,&nbsp;Dayou Luo ,&nbsp;Abhinav G. Kamath ,&nbsp;Samet Uzun ,&nbsp;Taewan Kim ,&nbsp;Behçet Açıkmeşe","doi":"10.1016/j.automatica.2025.112464","DOIUrl":"10.1016/j.automatica.2025.112464","url":null,"abstract":"<div><div>We present continuous-time successive convexification (<span>ct- scvx</span> ), a real-time-capable solution method for constrained trajectory optimization, with continuous-time constraint satisfaction and guaranteed convergence. The proposed solution framework only relies on first-order information, and it combines several key methods to solve a large class of nonlinear optimal control problems: (i) exterior penalty-based reformulation of the path constraints; (ii) generalized time-dilation; (iii) multiple-shooting discretization; (iv) <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span>-exact penalization of the nonconvex constraints; and (v) the prox-linear method, a sequential convex programming (SCP) algorithm for convex-composite minimization. The proposed reformulation of the path constraints enables continuous-time constraint satisfaction even on sparse temporal discretization grids and obviates the need for mesh-refinement heuristics. Through the prox-linear method, we guarantee that: (i) <span>ct-scvx</span> converges to stationary points of the penalized problem; (ii) the converged stationary points that are feasible for the discretized and control-parameterized optimal control problem are also Karush–Kuhn–Tucker (KKT) points. Furthermore, we specialize this property to global minimizers of convex optimal control problems and obtain stronger convergence results by exploiting convexity. In addition to theoretical analysis, we demonstrate the effectiveness and real-time performance of <span>ct-scvx</span> by means of numerical examples from real-world optimal control applications: dynamic obstacle avoidance, and 3-degree-of-freedom (3-DoF) and 6-DoF autonomous rocket landing.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"180 ","pages":"Article 112464"},"PeriodicalIF":4.8,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144548522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Minimizing energy consumption of collaborative deployment and task offloading in two-tier UAV edge computing networks","authors":"Yixuan Fang ,&nbsp;Zhufang Kuang ,&nbsp;Haobin Wang ,&nbsp;Siyu Lin ,&nbsp;Anfeng Liu","doi":"10.1016/j.sysarc.2025.103511","DOIUrl":"10.1016/j.sysarc.2025.103511","url":null,"abstract":"<div><div>Multi-Unmanned Aerial Vehicle (UAV)-supported Mobile Edge Computing (MEC) can meet the computational requirements of tasks with high complexity and latency sensitivity to compensate for the lack of computational resources and coverage. In this paper, a multi-user and multi-UAV MEC networks is built as a two-tier UAV system in a task-intensive region where base stations are insufficient, with a centralized top-center UAV and a set of distributed bottom-UAVs providing computing services. The total energy consumption of the system is minimized by jointly optimizing the task offloading decision, 3D deployment of two-tier UAVs, the elevation angle of the bottom UAV, the number of UAVs, and computational resource allocation. To this end, an algorithm based on Differential Evolution and greedy algorithm with the objective of minimizing Energy Consumption (DEEC) is proposed in this paper. The algorithm uses a two-tier optimization framework where the upper tier uses a population optimization algorithm to solve for the location and elevation angle of the bottom UAV and the number of UAVs based on the actual ground equipment and the lower tier uses clustering and greedy algorithms to solve for the position of the top UAV, the offloading decision of the task, and the allocation of computational resources based on the results of the upper layer. The simulation results show that the algorithm effectively reduces the total energy consumption of the system while satisfying the task computation success rate and time delay.</div></div>","PeriodicalId":50027,"journal":{"name":"Journal of Systems Architecture","volume":"167 ","pages":"Article 103511"},"PeriodicalIF":3.7,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A secure distributed resolution model for industrial internet identifier based on ordered multi-group signature","authors":"Peng Yang ,&nbsp;Zhuoyang Xie ,&nbsp;Hongmei Pei ,&nbsp;Tianwai Zhou ,&nbsp;Kun Song","doi":"10.1016/j.jisa.2025.104143","DOIUrl":"10.1016/j.jisa.2025.104143","url":null,"abstract":"<div><div>The security of the industrial Internet identifier resolution system is critical to ensuring the circulation of data in industrial production. Most existing schemes mainly use blockchain to solve problems such as a single point of failure and the unfair interests of multiple parties in the identifier resolution system. However, these schemes usually ignore the security of source data and transmission of the identifiers, which makes the identifiers vulnerable to manipulation or privacy disclosure. To address these issues, we propose a secure distributed resolution model for industrial Internet identifier based on ordered multi-group signature named SDRMI-OMGS. Specifically, a novel resolution model for industrial Internet identifier is proposed for enhancing the security of the identifiers in SDRMI-OMGS, which includes the Ordered Multi-Group Signature (OMGS) and the improved identifier encoding scheme. We conceive an authentication mechanism with OMGS to achieve trusted authentication of the identifiers and users during identifier resolution. Moreover, we utilize the confidentiality of asymmetric encryption and the immutability of blockchain to implement an identifier encoding scheme, which prevents the identifiers from manipulation or privacy disclosure during transmission. Finally, we prove the security of OMGS in SDRMI-OMGS based on the assumption of the hardness of the Elliptic Curve Discrete Logarithm Problem (ECDLP). Through experiments on the group signature, compared with the baselines, the extensive results show that the signature efficiency and verification of our scheme are increased by 67%, 40%, 58%, 35%, respectively in case of different members and groups.</div></div>","PeriodicalId":48638,"journal":{"name":"Journal of Information Security and Applications","volume":"93 ","pages":"Article 104143"},"PeriodicalIF":3.8,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Augmenting TCP Communication Efficiency in Cognitive Radio Networks Using Iterative Dimensional Neural Optimization","authors":"Manoj Kumar Chaudhary,&nbsp;Ashutosh Kumar Bhatt","doi":"10.1002/dac.70158","DOIUrl":"https://doi.org/10.1002/dac.70158","url":null,"abstract":"<div>\u0000 \u0000 <p>The increasing interest in data-driven applications in the dynamic wireless settings has further urged the requirement of efficient bandwidth exploitation and fair load distribution in cognitive radio (CR) networks. Conventional TCP communication is exposed to serious difficulties in these networks because of the heterogeneity in the spectrum, uncertain activity by primary users, and changing channel conditions. To overcome these issues, this work introduces a new Iterative Dimensional Neural Optimization (IDNO) paradigm capable of optimizing TCP performance using adaptive, cross-layer optimization. The main scientific contribution of IDNO is its Transformer-augmented Efficiency Prediction Model, which can precisely predict network capacity based on past channel information and instantaneous feedback from lower network layers. This predictive model supports IDNO's dynamic and iterative optimization of its key parameters such as relay node selection, power allocation, and frame size for maximum TCP rate with the promise of zero interference and high-efficiency utilization of spectrum resources. IDNO is empirically validated via simulations and experimental work. IDNO shows improvements as high as 51% when simulated under optimal laboratory-like situations, whereas 30% improves when under natural operating conditions in realistic settings. These findings prove the resilience and versatility of IDNO in coping with the dynamic characteristic of CR networks. In addition, the scheme attains an accuracy of throughput prediction of 2% error, exceeding traditional optimization techniques. With iterative optimization integrated with predictive modeling, IDNO builds a robust and effective solution towards enhancing TCP communication in spectrum-sharing networks, providing contributions to advances in spectrum efficiency, network reliability, and energy-efficient transmission strategy.</p>\u0000 <p>The IDNO paradigm enhances TCP communication in cognitive radio (CR) networks by addressing spectrum heterogeneity, primary user interference, and dynamic channel conditions. The Transformer-Augmented Efficiency Prediction Model predicts network capacity using historical data and real-time feedback. IDNO optimizes relay node selection, power allocation, and frame size through an iterative process, ensuring zero interference and high efficiency. Performance results demonstrate a 51% improvement in optimal conditions, 30% in real-world settings, and ≤ 2% error in throughput prediction, contributing to spectrum efficiency, network reliability, and energy-efficient transmission strategies in CR networks.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 12","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Learning Simple Causal Structures1","authors":"Dan Geiger, Azaria Paz, Judea Pearl","doi":"10.1002/j.1098-111x.1993.tb00005.x","DOIUrl":"https://doi.org/10.1002/j.1098-111x.1993.tb00005.x","url":null,"abstract":"Humans use knowledge of causation to derive dependencies among events of interest. The converse task, that of inferring causal relationships from patterns of dependencies, is far less understood. This article established conditions under which the directionality of some dependencies is uniquely dictated by probabilistic information—an essential prerequisite for attributing a causal interpretation to these dependencies. An efficient algorithm is developed that, given data generated by an undisclosed simple causal schema, recovers the structure of that schema, as well as the directionality of all links that are uniquely orientable. A simple schema is represented by a directed acyclic graph (dag) where every pair of nodes with a common direct child have no common ancestor nor is one an ancestor of the other. Trees, singly connected dags, and directed bi‐partite graphs are examples of simple dags. Conditions ensuring the correctness of this recovery algorithm are provided.","PeriodicalId":14089,"journal":{"name":"International Journal of Intelligent Systems","volume":"21 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144547052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Operator Assistant Systems: An Experimental Approach Using a Telerobotics Application*","authors":"Guy A. Boy, Nathalie Mathé","doi":"10.1002/j.1098-111x.1993.tb00006.x","DOIUrl":"https://doi.org/10.1002/j.1098-111x.1993.tb00006.x","url":null,"abstract":"This article presents a knowledge‐based system methodology for developing Operator Assistant (OA) systems in dynamic and interactive environments. Recent results in human error studies show that automation appears to be the most critical factor in human‐machine interaction problems. This is a problem both of training and design, which is the subject of this article. Design includes both design of the system to be controlled and design of procedures for operating this system. A specific knowledge representation is proposed for representing the corresponding system and operational knowledge. This representation is based on the situation recognition and analytical reasoning paradigm (SRAR). It tries to make explicit common factors involved in both human and machine intelligence, including perception and reasoning. An OA system based on this representation has been developed for space telerobotics. Simulations have been carried out with astronauts and the resulting protocols have been analyzed. Results show the relevance of the approach and have been used for improving the knowledge representation and the OA architecture. © 1993 John Wiley &amp; Sons, Inc.","PeriodicalId":14089,"journal":{"name":"International Journal of Intelligent Systems","volume":"48 1","pages":""},"PeriodicalIF":7.0,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144547053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MRTI-CR: A model based on multi-relationship and time-aware interest for personalized course recommendation","authors":"Shiyi Huang ,&nbsp;Yongquan Dong ,&nbsp;Ziyin Wang ,&nbsp;Nan Zhou ,&nbsp;Yuchao Ping","doi":"10.1016/j.engappai.2025.111560","DOIUrl":"10.1016/j.engappai.2025.111560","url":null,"abstract":"<div><div>With the advancement of information technology, Massive Open Online Course (MOOC) platforms offer students a diverse selection of courses but also introduce the challenge of “course overload”. Most existing course recommendation methods primarily model students’ interactions with courses implicitly, overlooking the rich multi-relationships between different entities and also failing to account for the impact of students’ evolving learning interests, particularly the influence of time on course selection behavior. To address these limitations, we propose a model based on <strong>M</strong>ulti-<strong>R</strong>elationship and <strong>T</strong>ime-aware <strong>I</strong>nterest for personalized <strong>C</strong>ourse <strong>R</strong>ecommendation(MRTI-CR), which effectively integrates heterogeneous relationships and dynamic interest evolution. Our approach extracts global features of users and courses by constructing a heterogeneous information network and leveraging a meta-path-guided graph convolutional network, such as prerequisite relationship meta-paths. Furthermore, to enhance the utilization of temporal information, we design a dynamic interest extraction module based on a time-aware Transformer. This module incorporates time-interval-aware positional encoding and optimizes multi-head attention using temporal weights, enabling the dynamic modeling of students’ learning interests. Experiments conducted on the MOOCCube public dataset demonstrate that MRTI-CR outperforms existing baseline models across multiple evaluation metrics in the course recommendation task.</div></div>","PeriodicalId":50523,"journal":{"name":"Engineering Applications of Artificial Intelligence","volume":"159 ","pages":"Article 111560"},"PeriodicalIF":7.5,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144534451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}