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A novel hybrid network optimization model for printed circuit boards recycling: a circular economy perspective

CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY 2021年第10期23卷 2989-3013页

作者： Yildizbasi, Abdullah Arioz, Yagmur Ankara Yildirim Beyazit Univ Dept Ind Engn TR-06010 Ankara Turkey

The recycling of printed circuit boards, which accounts for a considerable monetary value in waste electrical and electronic equipment, has long been ignored due to the serious challenges in collection, dismantling, and recycling processes. In this study, the open-loop and closed-loop supply chain involving circular economy objectives is designed in order to increase the recyclability of valuable metals including gold, silver, copper, and palladium. In this regard, a mixed-integer linear programming model, which aims at maximizing the profit from the flow in the supply chain network, is developed. The model is tested with actual data obtained from a printed circuit board firm in Turkey that aims an optimal distribution in its supply chain. The results reveal that the product/material flows, which have an impact on the revenues, are among the most important factors affecting the profitability. According to results, the circular economy objectives increase the revenue obtained in the hybrid open-loop and closed-loop supply chain. Besides, the boundaries of the proposed model are tested with sensitivity analyses, and the results are discussed extensively with conclusions on managerial implications.

关键词： Circular Economy Open-Loop Supply Chain Closed-Loop Supply Chain mixed integer linear programming Sustainability Printed Circuit Board

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A mixed integer programming Approach for the Resilience-Oriented Train Rescheduling Optimization in Railway Networks

A Mixed Integer Programming Approach for the Resilience-Orie...

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Chinese Automation Congress (CAC)

作者： Xianliang Ren Tao Tang Jiateng Yin State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China

ISBN: (纸本)9781665426480

Rail traffic control has received increasing attention in recent years, due to the destructive disruptions caused by floods, fires and equipment failures, etc. In this paper, we propose a resilience-oriented train rescheduling framework, which helps the rail transit system recover to the normal state as soon as possible in case of disruptions. Specifically, we first construct an event-activity network, in which the arrival and departure of trains are modeled as a set of events. Several groups of decision variables and linear constraints are denoted to model the rescheduling of trains. Considering the use of short-turning train rescheduling strategy and additional backup trains, we then formulate the problem into a mixed-integer linear programming (MILP) model, where the objective is to minimize the total delay time of trains against disruptions. Finally, numerical experiments are conducted to verify the effectiveness of our approach.

关键词： Rails integer programming Redundancy Rail transportation Numerical models mixed integer linear programming Delays

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Integrated Framework for Task Scheduling and Attitude Control of Multiple Agile Satellites

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JOURNAL OF AEROSPACE INFORMATION SYSTEMS 2021年第8期18卷 539-552页

作者： Kim, Junhong Ahn, Jaemyung Korea Adv Inst Sci & Technol Dept Aerosp Engn 291 Daehak Ro Daejeon 34141 South Korea

This paper introduces an optimal scheduling framework for the Earth observation tasks of multiple agile satellites based on nonlinear modeling of attitude change time for the task transition. An attitude control module using a quaternion feedback constructs the database storing the time to complete the attitude change maneuver for a given initial and final attitude pair. A mixed-integer linear programming (MILP) formulation for optimal satellite task scheduling based on the generated transition time database is developed. The database can accurately estimate the task transition time and ensure the feasibility of the obtained solution. A P-MILP heuristic, which can prune out unnecessary constraints of the original MILP formulation and obtain near-optimal solutions for large problem instances, is proposed. A comprehensive case study on the task scheduling to operate agile satellites validates the proposed framework and heuristic.

关键词： Attitude Control System Satellite Constellations Quaternions Earth mixed integer linear programming Earth Observation Satellite Feedback Control C programming Language Earth Centered Inertial linear programming

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Minimizing Carbon Emission in Hybrid Flow Shop Scheduling: A Comparative Analysis of Flow-based and Set Partitioning Formulations

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Procedia Computer Science 2024年 232卷 2831-2840页

作者： Guilherme de Souza Ferreira Geraldo Robson Mateus Martín Gómez Ravetti Departamento de Engenharia de Produção Universidade Federal de Minas Gerais Brazil Departamento de Ciências da Computação Universidade Federal de Minas Gerais Brazil

This article addresses the Hybrid Flow Shop Green Scheduling Problem with Sequence and Machine Dependent Setup Times (HFSGSP-SMDST) in the context of Industry 4.0. The objective is to minimize carbon emission while optimizing scheduling. Two mathematical formulations, a flow-based positional formulation (FB) and a set partitioning positional formulation (HCG), are proposed to provide tighter lower bounds. The FB formulation is solved using a commercial solver, while the HCG algorithm incorporates an Iterated Local Search (ILS) to generate initial solutions and an upper bound for the problem. Computational experiments demonstrate that HCG achieves better lower bounds, although it requires more time compared to FB. The proposed algorithms offer valuable solutions for carbon emission optimization and scheduling in Industry 4.0, with a trade-off between lower bounds and convergence speed.

关键词： green scheduling hybrid flow shop setup times unrelated parallel machines mixed integer linear programming hybrid column generation

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Superstructure Optimization of International Hydrogen Supply Chain with Technological Options

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IFAC-PapersOnLine 2024年第14期58卷 811-816页

作者： Juyeong Jung Jay H. Lee Wonsuk Chung Seongmin Heo Department of Chemical and Biomolecular Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon Korea Department of Chemical and Materials Science and of Aerospace and Mechanical Engineering University of Southern California Los Angeles CA 90007 USA Clean Energy Research Center Korea Institute of Science and Technology (KIST) 02792 Seoul Korea

In the pursuit of reducing carbon emissions, the integration of renewable energy into society’s energy portfolio plays a crucial role despite challenges tied to their inherent unpredictability and seasonal variations. Hydrogen, as a mean of storing and transporting renewable energy becomes crucial in addressing these challenges. Notwithstanding its potential, the misalignment of cost-competitive hydrogen production hubs with demand centers calls for a thorough examination of global hydrogen distribution. The versatility of hydrogen transportation (e.g., pipelines, ships, trucks) and various forms like compressed hydrogen, liquid hydrogen, ammonia, and liquid organic hydrogen carriers (LOHC) adds complexity to designing an economically efficient hydrogen supply chain (HSC). Addressing previous scholarly limitations focused on existing technologies, this study advocates for a superstructure-based modeling approach for HSC that includes promising technologies. Through a case study involving a production site in the Middle East and a demand site in Texas, a dedicated HSC superstructure network is formulated, facilitating the identification of cost-effective hydrogen supply pathways using mixed integer linear programming. Ultimately, this effort aims to establish a comprehensive framework to discern the most sustainable and financially viable technologies, identifying the optimal configuration within the HSC.

关键词： Hydrogen supply chain Process modeling Superstructure optimization mixed integer linear programming

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A Multi-period Optimization Model for the Design of an Off-Grid Micro Hydro Power Plant with Profitability and Degradation Considerations

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PROCESS INTEGRATION AND OPTIMIZATION FOR SUSTAINABILITY 2021年第2期5卷 193-205页

作者： Hernandez, Juan Carlo Penas, Carlos Jan Tiu, Adrianne Ressa Sy, Charlle De La Salle Univ Ind Engn Dept 2401 Taft Ave Manila 0922 Philippines

Micro hydroelectric power is a clean and efficient source of energy that has been used for the electrification of rural off-grid communities. However, numerous micro hydro installations have failed as caused by factors such as poor site selection and uneconomical design of materials, among others. A multi-period mixed integer linear programming model for the design of an off-grid micro hydro power plant is then developed. The proposed model is able to provide technical specifications such as the penstock dimensions, turbine choice, weir height, and site choice in order to fulfill a community's demand while simultaneously maximizing the net present value of the investment. The model may choose among different productive end uses, with each being subject to a respective investment cost as well as a set-up time and degradation rate. Computational experiments demonstrate the different capabilities of the model to address real-life scenarios such as population growth and streamflow variability. An increase in energy consumption due to population growth leads to the requirement of a more powerful turbine. Capacity limitations likewise prevent the community to invest in productive end usage. Meanwhile, streamflow variability potentially reduces the capability of the power plant to produce electricity. In these instances, batteries had to simultaneously be used in order to augment the increase in energy requirement.

关键词： mixed integer linear programming Hydroelectric power Off-grid micro hydro power plant Multi-period Uncertainty

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A theoretical and computational study of green vehicle routing problems

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JOURNAL OF COMBINATORIAL OPTIMIZATION 2023年第5期45卷 118-118页

作者： Andrade, Matheus Diogenes Usberti, Fabio Luiz Univ Estadual Campinas Inst Comp Univ City 1251 BR-13083852 Campinas SP Brazil

This work investigates green vehicle routing problems (G-VRPs). GVRPs are NP-hard problems embodying the motivation, concepts, and advances of green logistics in the vehicle routing problem (VRP) domain. To address the shorter autonomy of electric vehicles, the G-VRP considers Alternative Fuel Stations (AFSs) that can be used to refuel vehicles in travel. Originally, the G-VRP prohibits consecutive AFS visits, i.e., a solution cannot have an edge between two AFSs. Here, besides the original G-VRP, we also consider the variant in which consecutive AFS visits are allowed. This research proposes combinatorial properties, concerning the number of visits to the AFSs, bounds on fuel consumption, and bounds on the number of routes and their cost. Furthermore, this research proposes valid inequalities, MILP formulations, preprocessing conditions, and lower bounds which strengthen the mathematical formulations for both G-VRP versions, thus improving their exact solution. The proposed methodologies were evaluated with extensive computational experiments. The results are analyzed and discussed, and conclusions on the benefits of the contributions are presented.

关键词： mixed integer linear programming Mathematical programming Vehicle routing problem Combinatorial optimization Green logistics

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An MILP model for reliability-based placement of recloser, sectionalizer, and disconnect switch considering device relocation

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SUSTAINABLE ENERGY GRIDS & NETWORKS 2023年 35卷

作者： Azarhazin, Saeed Farzin, Hossein Mashhour, Elaheh Shahid Chamran Univ Ahvaz Fac Engn Ahvaz *** Iran

By optimal placement of protection and switching devices in distribution networks, maximum improvement in system reliability can be achieved with minimum equipment cost. This study presents a mathematical model for simultaneous placement of recloser, sectionalizer and disconnect switch (including remote-controlled and manual switches). A mathematical model for sectionalizer's automatic operation in coordination with the upstream recloser is proposed in this paper. In addition, a new model is introduced for relocation of the existing equipment, and the effect of tie switch is also addressed. The model is formulated in the form of a mixed integer-linear programming (MILP) problem, whose global optimal solution is guaranteed. The objective of the presented model is to find the optimal device locations, in such a way that the equipment's investment, maintenance and relocation costs, as well as the customer interruption costs associated with permanent and temporary faults are minimized. To validate the developed model, it has been implemented on Bus 4 of Roy Billinton test system (RBTS), and it is solved using GAMS software and CPLEX solver. The obtained results from different scenarios and sensitivity analyses confirm the correct and justifiable performance of the model.& COPY;2023 Elsevier Ltd. All rights reserved.

关键词： Switch placement Automatic sectionalizer Relocation Tie switch mixed integer linear programming Distribution network reliability

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A Scalable Buffer Queue Sizing Algorithm for Latency Insensitive Systems

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IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS 2021年第11期40卷 2386-2399页

作者： Maji, Supriyo Koh, Cheng-Kok Purdue Univ Dept Elect & Comp Engn W Lafayette IN 47907 USA Cadence Design Syst San Jose CA 95134 USA

Timing violations in high performance communication channels in system-on-chips (SoC) may occur in the late stages of the physical design process. To address that, latency insensitive systems (LISs) employ pipelining in the communication channels through the insertion of relay stations. Although the functionality of an LIS is robust with respect to the communication latencies, imbalances in relay station insertion may degrade the throughput of the system. While having a large number of buffer queues can eliminate such performance loss, the system may not have adequate area to accommodate these buffers. The problem of buffer queue sizing for maximizing throughput while meeting buffer area constraints has been solved using a mixed-integer linear program (MILP) formulation;however, such an approach is not scalable. In this work, we formulate the buffer queue sizing problem as a parameterized graph optimization problem where for every communication channel there is a parameterized edge with buffer counts as the edge weight. We then use a minimum cycle mean algorithm to determine from which edges buffers can be removed safely. Experimental results on large LISs suggest that the proposed approach is scalable. Moreover, quality of the solutions, in terms of the throughput and the size of buffer queues, is observed to be as good as that of the MILP-based approach.

关键词： Buffer queue sizing graph algorithms latency insensitive systems minimum balancing minimum cycle mean mixed integer linear programming throughput optimization timing optimization

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Solving a real-world Locomotive Scheduling Problem with Maintenance Constraints

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2021年 150卷 386-409页

作者： Frisch, Sarah Hungerlaender, Philipp Jellen, Anna Primas, Bernhard Steininger, Sebastian Weinberger, Dominic Alpen Adria Univ Dept Math Klagenfurt Austria Rail Cargo Grp Vienna Austria Hex GmbH Klagenfurt Austria

This work addresses the Locomotive Scheduling Problem with Maintenance Constraints (LSPM). The basic Locomotive Scheduling Problem (LSP), which depicts one of the most crucial optimization problems occurring in the railway industry, aims at assigning a fleet of locomotives to a set of scheduled trains such that the overall costs are minimized. As the rolling stock represents one of the main costs of a rail company, the focus lies on maximizing the utilization of the locomotives. This requires the incorporation of special maintenance constraints that increase the computational difficulty of the problem significantly. In our previous work, we proposed a mixed-integer linear programming formulation for solving the LSPM and continue in this paper by investigating different heuristic solution approaches, i.e., an Overlapping Rolling Horizon Approach and a Two-Stage Matheuristic (2SMH). In the objective function, realistic costs for deadheading, the number of used locomotives and maintenance jobs are taken into account. An extensive computational study is conducted on instances with up to 2,290 trains derived from real-world data provided by RCA, the largest Austrian rail company for freight transportation. All solution approaches are analyzed in detail and compared against each other in order to show their benefits and disadvantages. We show that our approaches are capable of delivering high-quality solutions within short computation times. In fact, the performance of the 2SMH qualifies it to form the basis of a large scale real-time application to support railroad managers in their daily operations.

关键词： Locomotive Scheduling Problem Maintenance constraints mixed integer linear programming

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