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IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Kong, Weijiang Nabi, Majid Goossens, Kees Eindhoven Univ Technol Dept Elect Engn Eindhoven Netherlands

ISBN: (数字)9781665499965

ISBN: (纸本)9781665499965

In the automotive domain, Ethernet Audio Video Bridging (AVB) provides service guarantees for real-time traffic. Its configuration synthesis requires routing the flows and allocating the bandwidth for Credit Based Shaping (CBS). Current approaches typically employ deadline-oblivious bandwidth allocation and rely on routing to establish deadline guarantees. But the worst-case delay of AVB flows requires complex analysis. Thus, routing integrated with the delay analysis either supports limited Stream Reservation (SR) classes or suffers significant timing overhead. To enable efficient run-time flow setup, we propose SynAVB, a tool to synthesize the configuration of Ethernet AVB, which establishes deadline awareness in bandwidth allocation. SynAVB supports an arbitrary number of SR classes and processes them one by one. For the flows in an SR class, it first performs a deadline-oblivious routing based on mixed integer linear programming (MILP) to guarantee the necessary bandwidth required by the flows. Then, a deadline-aware slope allocation algorithm computes the bandwidth required on every link to satisfy the deadline of all flows. Our experiment demonstrates that, given the same routes, the deadline-aware bandwidth allocation results in fewer flows violating the deadline compared with other allocation strategies. Moreover, SynAVB can guarantee the deadline of more flows while its run-time is up to 14.3x faster than the state-of-the-art approaches.

关键词： Ethernet Bandwidth Channel allocation Routing Real-time systems Delays mixed integer linear programming

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The berth allocation and quay crane assignment problem with crane travel and setup times

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COMPUTERS & OPERATIONS RESEARCH 2024年 162卷

作者： Correcher, Juan F. Perea, Federico Alvarez-Valdes, Ramon Univ Valencia Dept Estadist & Invest Operat Doctor Moliner 50 Burjassot 46100 Spain Univ Seville Dept Matemat Aplicada 2 Avda Reina Mercedes S-N Seville 41012 Spain Inst Matemat IMUS Avda Reina Mercedes S-N Seville 41012 Spain

In this paper, we propose a new approach for including quay crane travel and setup times in the berth allocation and quay crane assignment problem. We first develop a new mixed integer linear programming model (MILP) for the problem without setups (BACASP), in which berthing positions and times are considered as continuous variables. Several groups of valid inequalities are also set forth. Then, for the BACASP with crane travel and setup times, which we denote as BACASP-S, we propose two MILPs: the first is based on the previous BACASP formulation and the second on routing formulations. Due to the complexity of the BACASP-S, we also propose a genetic algorithm and an exact approach which combines various MILPs with the genetic algorithm. All methods and valid inequalities are computationally tested over two different sets of randomly generated instances. According to the results, the models and algorithms can optimally solve, in less than one hour, BACASP-S instances of up to 40 vessels within a quay one kilometer long and a time horizon of one week. Additionally, extensive experiments were conducted on a new large set of instances to assess the effect of various BACASP-S input parameters on the computation effort required to solve the problem. Ceteris paribus, the computational effort required seems to increase with decreasing number of cranes, while vessel processing times and crane setup times seem not to affect it.

关键词： Berth allocation Quay crane assignment Setup time mixed integer linear programming Combinatorial optimization Port logistics Container terminal

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A genetic algorithm with critical path-based variable neighborhood search for distributed assembly job shop scheduling problem

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SWARM AND EVOLUTIONARY COMPUTATION 2024年 85卷

作者： Tian, Shichen Zhang, Chunjiang Fan, Jiaxin Li, Xinyu Gao, Liang Huazhong Univ Sci & Technol State Key Lab Intelligent Mfg Equipment & Technol Wuhan 430074 Peoples R China

Production scheduling in distributed manufacturing systems has become an active research field, where largesized complicated products, such as airplanes and ships, are taken as the primary focus. This paper investigates a distributed assembly job shop scheduling problem (DAJSP) which consists of two production phases. The first stage processes components in several job shops, and the second stage assembles the processed parts into final products. First, a mixed integer linear programming (MILP) model is established to describe the problem with minimizing maximum completion time and find optimal schedules for small-scale scenarios. Afterwards, a genetic algorithm with variable neighborhood search (GA-VNS) is proposed to address more complex instances, which adopts the genetic algorithm as the main framework and employs the variable neighborhood search for exploration. A problem -specific three -vector encoding scheme is designed to represent three decision -making processes of the DAJSP accordingly. To improve candidate solutions, a disjunctive graph model for DAJSP is formulated and three critical path -based neighborhood structures which directly perform on encoding vectors are designed. Numerical experiments are conducted on four groups of instances with different scales and the experimental results demonstrate the effectiveness of the proposed MILP model and GA-VNS. To sum up, the proposed GA-VNS shows the best performance on 30 instances out of 40 instances, while the superior stability has also been proved by statistical tests. In addition, two complicated DAJSP cases are abstracted from an enterprise for fabricating large complex components to further validate the GA-VNS.

关键词： Distributed assembly job shop scheduling Genetic algorithm Variable neighborhood search mixed integer linear programming Critical path

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Optimizing perishable food products across states: A multi objective evolutionary algorithm for surplus to deficit transportation

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2024年第PartA期137卷

作者： Karanam, Malleswari Krishnanand, Lanka Manupati, Vijaya Kumar Varela, M. L. R. NIT Dept Mech Engn Warangal 506004 Telangana India Indian Inst Management Operat & Supply Chain Div Mumbai 400087 India Univ Minho Dept Prod & Syst Guimaraes Portugal

Ensuring the seamless flow of goods from farmer to stakeholder is paramount especially considering the facts such as demand fluctuations, quantity availability, vehicle capacity, inventory limits and truck preferences. In this paper, we proposed a mixed integer linear programming (MILP) model for distributing perishable food goods from surplus states to surplus and deficit state wholesalers in the Indian subcontinent, with the goal of minimizing total cost (fixed, variable, and operational) and transportation time. To ensure product delivery on time, we looked at various scenarios including a case with real-life constraints. Solving this computationally complex task with conflicting objectives in a reasonable time is difficult. To handle the aforementioned multi-objective problem, we proposed an evolutionary algorithm based modified non-dominated sorting genetic algorithm II (MNSGA-II). Furthermore, the suggested algorithm's performance is tested against the most extensively used multi-objective algorithm, Non-dominated Sorting Genetic method-II (NSGA-II). According to the findings, the proposed MNSGA-II outperforms practically all instances.

关键词： Perishable food Multi-objective Evolutionary algorithm mixed integer linear programming Non-dominated sorting genetic algorithm-II Modified non-dominated sorting genetic algo- rithm-II

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Optimal Location of Normally Closed Switches in Medium Voltage Distribution Networks 9

Optimal Location of Normally Closed Switches in Medium Volta...

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9th International Conference on Electrical and Electronics Engineering (ICEEE)

作者： Canizes, Bruno Soares, Joao Ramos, Sergio Chaves, Juliana Vale, Zita Forouzandeh, Zahra GECAD Res Grp Polytechn Porto ISEP IPP Porto Portugal

ISBN: (纸本)9781665467544

This research paper presents a deterministic optimization technique for the optimal location of normally closed switches on a realistic medium voltage distribution network located in Portugal. The goal is to minimize the expected outage costs to consumers in conjunction with normally closed switches capital investment, installation, and annual operation and maintenance costs, improving at the same time the level of reliability and service quality of distribution networks. The optimization approach is developed as mixed-integer linear programming using CPLEX solver in the TOMLAB optimization tool. The global solution obtained was successfully tested and validated with real data of the above-mentioned Portuguese network. The presented results indicate the accuracy and efficiency of the proposed method.

关键词： distribution networks mixed integer linear programming normally closed switch placement reliability

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Design a sustainable supply chain for the textile and clothing industry with consideration of carbon emissions 10th

Design a sustainable supply chain for the textile and clothi...

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10th IFAC Triennial Conference on Manufacturing Modelling, Management and Control (MIM)

作者： Mezatio, Eric Papain Aghelinejad, Mohammadmohsen Amodeo, Lionel Ferreira, Isabelle Univ Technol Troyes 12 Rue Marie Curie F-10300 Troyes France Inst Francais Text & Habillement 270 Rue Faubourg Croncels F-10000 Troyes France

The clothing industry accounts for nearly 60% of the global textile industry. It is largely responsible for the consumption of non-renewable resources. According to studies, it is responsible for nearly 10% of greenhouse gas emissions in the world (Cuc and Vidovic (2014)). The aim of this article is to propose a planning approach that integrates two decision levels (strategic and tactical), using a new mixed integer linear programming model (MILP) that integrates carbon emissions in SCMP (Supply Chain Management Planning). This approach must be used in a general way in all SCMP industries for the control of carbon flows and resources. It could be used as a decision support tool to evaluate and monitor the effects of carbon emissions. This tool offer to the industrials the best choices at different stages (selection of suppliers, plants, transportation modes, storage etc.), with lower cost and carbon emissions. For this purpose, the approach is tested on several scenarios, based on severals literature case studies in the textile and clothing sectors. The results show that carbon price uncertainty would significantly influence the economic and environmental management of the supply chain, and the repartition of the manufacturing activity (insource or outsource). Over a range of carbon price scenarios, the results show a reduction over to 36% in carbon emissions in the supply chain. Copyright (C) 2022 The Authors.

关键词： Design supply chain textile and clothing industries mixed integer linear programming Economic and Environmental aspect

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Multi-criteria decision analysis for pharmaceutical supplier selection problem using fuzzyTOPSIS

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MANAGEMENT DECISION 2022年第3期60卷 806-836页

作者： Modibbo, Umar Muhammad Hassan, Musa Ahmed, Aquil Ali, Irfan Aligarh Muslim Univ Dept Stat & Operat Res Aligarh Uttar Pradesh India Modibbo Adama Univ Dept Stat & Operat Res Yola Nigeria Adamawa State Polytech Dept Stat Coll Sci & Technol Yola Nigeria

Purpose Supplier selection in the supply chain network (SCN) has strategic importance and involves multiple factors. The multi-criteria nature of the problem coupled with environmental uncertainty requires several procedures and considerations. The issue of decision-making in selecting the best among various qualified suppliers remains the major challenge in the pharmaceutical industry. This study investigated the multi-criteria multi-supplier decision-making process and proposed a model for supplier selection problems based on mixed-integer linear programming. Design/methodology/approach The concept of principal component analysis (PCA) was used to reduce data dimensionality, and the four best criteria have been considered and selected. The result is subjected to decision-makers' (DMs') reliability test using the concept of a triangular fuzzy number (TFN). The importance of each supplier to each measure is established using fuzzy technique for order preference by similarity to an ideal solution approach, and the suppliers have ranked accordingly. Findings This study proposes a mixed integer linear programming model for supplier selection in a pharmaceutical company. The effectiveness of the proposed model has been demonstrated using a numerical example. The solution shows the model's applicability in making a sound decision in pharmaceutical companies in the space of reality. The model proposed is simple. Readily commercial packages such as LINDO/LINGO and GAMS can solve the model. Research limitations/implications This research contributed to the systematic manner of supplier selection considering DMs' value judgement under a fuzzy environment and is limited to the case study area. However, interested researchers can apply the study in other related manufacturing industries. However, the criteria have to be revisited to suit that system and might require varying ratings based on the experts' opinions in that field. Practical implications This work suggests more in

关键词： Multi-criteria decision-making Supplier selection Fuzzy TOPSIS Triangular fuzzy number Principal component analysis mixed integer linear programming

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A Matheuristic based on Ant Colony System for the Combined Flexible Jobshop Scheduling and Vehicle Routing Problem 10th

A Matheuristic based on Ant Colony System for the Combined F...

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10th IFAC Triennial Conference on Manufacturing Modelling, Management and Control (MIM)

作者： Torres-Tapia, William Montoya-Torres, Jairo R. Ruiz-Meza, Jose Belmokhtar-Berraf, Sana Univ La Sabana Res Grp Logist Syst Km 7 Autopista Norte Bogota Dc Chia Colombia Univ Gustave Eiffel COSYS GREFTTIA ESIEE Paris 5 Blvd Descartes F-77454 Champs Sur Marne France

Nowadays, market behavior and globalization mean that end consumers are waiting very quickly for their orders to be delivered. This context forces companies to have high availability of finished products. For this reason, the industries that make up the supply chains are obliged to implement strategies to meet this customer need. One efficient practice is the integration of production and transportation activities. In the literature, few research works integrate the scheduling of production tasks with the vehicle routing. This paper aims at proposing a solution approach for the combined problem. The production system configuration is defined as a flexible jobshop, while the distribution problem is modeled as a vehicle routing problem. The proposed approach consists of two parts. First, production makespan is minimized through a hybrid algorithm based on ant colony system and local search. Then, the routing problem is solved optimally using mathematical programming in order to minimize the total travel time. Benchmark instances from the literature are adapted to deal with the combined problem. Experimental results show the effeciency and effectiveness of the proposed algorithm. Copyright (C) 2022 The Authors.

关键词： Flexible jobshop Vehicle Routing Problem Ant Colony Metaheuristic Local Search mixed integer linear programming

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Modeling Hybrid Renewable Energy Systems for Optimal Investment and Operational Decisions

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SN Computer Science 2022年第3期3卷 246页

作者： Levy, Roberto Brodsky, Alexander Computer Science Department George Mason University Fairfax 22030 VA United States

This paper focuses on making optimal investment and operational recommendations for a Hybrid Renewable Energy System (HRES). For this purpose, we develop a modular composite analytic performance model for HRES investment, which is based on an extensible library of atomic component models, including power storage, generators, renewable sources, third-party contracts, and household consumption. The performance model is able to formally express feasibility constraints and different key performance indicators, including total cost of ownership, environment impact, and infrastructure resilience, as a function of investment and operational decision variables. Based on the performance model, we design and develop a decision guidance system to enable actionable investment recommendations that optimize total cost of ownership, subject to the operational constraints associated with the network. We demonstrate the model in a case study for a municipal electric utility. © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Hybrid renewable energy system Investment decision guidance mixed integer linear programming Optimization Power networks

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Assignment strategy and lane depth in homogeneous multi-deep shuttle-based S/R systems

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2025年

作者： Lupi, Giacomo Accorsi, Riccardo Battarra, Ilaria Guidani, Beatrice Manzini, Riccardo Sirri, Gabriele Univ Bologna Dept Ind Engn Bologna Italy

An automated vehicle storage and retrieval system (AVS/RS) is a widely used warehouse solution that adopts automated technologies to store and retrieve palletised unit loads. Several factors affect the performance of such shuttle-based systems in terms of productivity and space efficiency. This study focuses on the best achievable performance of nominal storage capacity saturation via assignment strategy selection and lane depth determination. These are the crucial aspects to consider when designing and configuring a homogeneous AVS/RS, where homogeneity means that the generic storage lane hosts unit loads (UL) of the same item. This study aims to introduce and apply an original mixed-integer linear programming model to optimise the space efficiency and storage capacity of a multi-deep tier-captive AVS/RS. A time-splitting methodology is introduced to obtain solutions for real applications. A multi-scenario analysis conducted on a case study demonstrates the effectiveness of the proposed model and solution methods.

关键词： Automated warehouses Multi-deep AVS/RS Assignment strategy Lane depth mixed integer linear programming Performance analysis

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