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22nd IEEE Annual International Symposium on Field-Programmable Custom Computing Machines ((FCCM)

作者： Rabozzi, Marco Lillis, John Santambrogio, Marco D. Politecn Milan Milan Italy Univ Illinois Chicago IL USA

ISBN: (纸本)9781479951116

The aim of this paper is to show a novel floorplanner based on mixed-integer linear programming (MILP), providing a suitable formulation that makes the problem tractable using state-of-the-art solvers. The proposed method takes into account an accurate description of heterogeneous resources and partially reconfigurable constraints of recent FPGAs. A global optimum can be found for small instances in a small amount of time. For large instances, with a time limited search, a 20% average improvement can be achieved over floorplanners based on simulated annealing. Our approach allows the designer to customize the objective function to be minimized, so that different weights can be assigned to a linear combination of metrics such as total wire length, aspect ratio and area occupancy.

关键词： Algorithm design and analysis Field programmable gate arrays Kernel linear programming Measurement Simulated annealing Wires FPGA Floorplanning Reconfigurable Computing Field programmable gate arrays Algorithm design and analysis simulated annealing circuit layout Rope ELECTRIC WIRE linear programming Kernel mixed integer linear programming

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A mixed integer linear programming formulation of closed loop layout with exact distances

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JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING 2013年第3期30卷 190-201页

作者： Niroomand, Sadegh Vizvari, Bela Istanbul Aydin Univ Dept Ind Engn Istanbul Turkey Eastern Mediterranean Univ Dept Ind Engn North Cyprus Turkey

In the layout problem of manufacturing cells, rectangular cells are to be positioned without overlapping. The objective is to minimize the total transportation cost, i.e. the sum of distances of all pairs of cells weighted by their flow values. The types of layouts are categorized according to the shape of the transportation system's track. In the case of a closed loop layout, the track has a rectangular shape. A common difficulty of all layout problems is the manner in which distances are measured. A frequently used approximation is the Manhattan distance. However, it is significantly shorter than the exact distance in many cases. Both the metaheuristics and exact models suggested by earlier studies use the Manhattan distance. In this paper, a new mathematical model is suggested for the closed loop layout with exact distances. Many feasible solutions are generated for benchmark problems that are competitive with the solutions provided by metaheuristics.

关键词： facility layout problem closed loop layout mixed integer linear programming

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Solving the quadratic assignment problem by means of general purpose mixed integer linear programming solvers

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ANNALS OF OPERATIONS RESEARCH 2013年第1期207卷 261-278页

作者： Zhang, Huizhen Beltran-Royo, Cesar Ma, Liang Rey Juan Carlos Univ Madrid Spain Univ Shanghai Sci & Technol Sch Management Shanghai Peoples R China

The Quadratic Assignment Problem (QAP) can be solved by linearization, where one formulates the QAP as a mixed integer linear programming (MILP) problem. On the one hand, most of these linearizations are tight, but rarely exploited within a reasonable computing time because of their size. On the other hand, Kaufman and Broeckx formulation (Eur. J. Oper. Res. 2(3):204-211, 1978) is the smallest of these linearizations, but very weak. In this paper, we analyze how the Kaufman and Broeckx formulation can be tightened to obtain better QAP-MILP formulations. As shown in our numerical experiments, these tightened formulations remain small but computationally effective to solve the QAP by means of general purpose MILP solvers.

关键词： Quadratic assignment problem mixed integer linear programming

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Multi-objective, multi-period optimization of biomass conversion technologies using evolutionary algorithms and mixed integer linear programming (MILP)

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APPLIED THERMAL ENGINEERING 2013年第2期50卷 1504-1513页

作者： Fazlollahi, Samira Marechal, Francois VERI F-78520 Limay France Ecole Polytech Fed Lausanne LENI IGM STI EPFL Stn 9 CH-1015 Lausanne Switzerland

The design and operation of energy systems are key issues for matching energy supply and demand. A systematic procedure, including process design and energy integration techniques for sizing and operation optimization of poly-generation technologies is presented in this paper. The integration of biomass resources as well as a simultaneous multi-objective and multi-period optimization, are the novelty of this work. Considering all these concepts in an optimization model makes it difficult to solve. The decomposition approach is used to deal with this complexity. Several options for integrating biomass in the energy system, namely back pressure steam turbines, biomass rankine cycles (BRC), biomass integrated gasification gas engines (BIGGE), biomass integrated gasification gas turbines, production of synthetic natural gas (SNG) and biomass integrated gasification combined cycles (BIGCC), are considered in this paper. The goal is to simultaneously minimize costs and CO2 emission using multi-objective evolutionary algorithms (EMOO) and mixed integer linear programming (MILP). Finally the proposed model is demonstrated by means of a case study. The results show that the simultaneous production of electricity and heat with biomass and natural gas are reliable upon the established assumptions. Furthermore, higher primary energy savings and CO2 emission reduction, 40%, are obtained through the gradual increase of renewable energy sources as opposed to natural gas usage. However, higher economic profitability, 52%, is achieved with natural gas-based technologies. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Poly-generation systems mixed integer linear programming Evolutionary algorithm Biomass conversion technologies CO2 mitigation

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Real-time train routing and scheduling through mixed integer linear programming: Heuristic approach

Real-time train routing and scheduling through mixed integer...

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5th International Conference on Industrial Engineering and Systems Management (IEEE IESM)

作者： Pellegrini, Paola Douchet, Guillaume Marliere, Gregory Rodriguez, Joaquin Univ Lille Nord France Ifsttar ESTAS F-59666 Lille France

ISBN: (纸本)9782960053241

In railway traffic management, when an unexpected event perturbs the system, finding an effective train routing and scheduling in real-time is a key issues. Making the right routing and scheduling decisions may have a great impact on the efficiency of the system in terms of delay propagation. However, the time available for making these decisions is quite short: in few minutes a viable set of routes and schedules must be delivered to the dispatching system. In this paper, we assess the performance of a mixed integer linear programming (MILP) formulation exploited as a heuristic approach: we seek for the best feasible solution given a limited and predefined computation time. We run an experimental analysis on instances representing traffic in the Lille Flandres station, France. The results show that the approach tested is very promising, often finding the optimal solution to the instances tackled. Moreover, we show how the performance can be improved by tuning the parameters of the MILP solver.

关键词： mixed integer linear programming scheduling system Network routing TRAIN Heuristics computational time optimal solution railway transportation management

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A mixed integer linear programming FORMULATION FOR THE SPARSE RECOVERY PROBLEM IN COMPRESSED SENSING

A MIXED INTEGER LINEAR PROGRAMMING FORMULATION FOR THE SPARS...

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IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Karahanoglu, N. Burak Erdogan, Hakan Birbil, S. Ilker TUBITAK BILGEM Adv Technol Res Inst Kocaeli Turkey Sabanci Univ Fac Engn & Nat Sci Istanbul Turkey

ISBN: (纸本)9781479903566

We propose a new mixed integer linear programming (MILP) formulation of the sparse signal recovery problem in compressed sensing (CS). This formulation is obtained by introduction of an auxiliary binary vector, where ones locate the recovered nonzero indices. Joint optimization for finding this auxiliary vector together with the underlying sparse vector leads to the proposed MILP formulation. By addition of a few appropriate constraints, this problem can be solved by existing MILP solvers. In contrast to other methods, this formulation is not an approximation of the sparse optimization problem, but is its equivalent. Hence, its solution is exactly equal to the optimal solution of the original sparse recovery problem, once it is feasible. We demonstrate this by recovery simulations involving different sparse signal types. The proposed scheme improves recovery over the mainstream CS recovery methods especially when the underlying sparse signals have constant amplitude nonzero elements.

关键词： compressed sensing l(0) norm minimization sparse signal recovery mixed integer linear programming branch-and-cut algorithm

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DETERMINATION OF THE PORT ATTRACTIVENESS USING mixed integer linear programming METHOD

DETERMINATION OF THE PORT ATTRACTIVENESS USING MIXED INTEGER...

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12th International Symposium on Operational Research (SOR '13)

作者： Kramberger, Tomaz Vizinger, Tea Intihar, Marko Chin, Anthony Univ Maribor Fac Logist Mariborska 7 Celje 3000 Slovenia Natl Univ Singapore Singapore 119077 Singapore

ISBN: (纸本)9789616165402

In this paper we present well know Port Choice Problem as a mixed integer linear Programing (MILP) problem. Using MILP we comapare North Adriatic ports with North European ports and determine their relative attractiveness for Bavarian shippers in case of importing containerized goods from far east. The results of the model show that despite better geographical position of North Adriatic ports Bavarian shippers are attracted to Nort European ports. The model also shows that land transport costs and subjective preferance rate play a large role in Port Choice.

关键词： mixed integer linear programming Port choice Port attractiveness

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Integrated Optimization Planning of Multiple Energy Stations for Low Carbon Operation

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CSEE Journal of Power and Energy Systems 2025年第2期11卷 815-825页

作者： Weijie Dong Keyan Liu Wanxing Sheng Beijing Information Science&Technology University Beijing 100192China China Electric Power Research Institute Beijing 100192China

Under the background of low-carbon demand, an integrated energy system is the main direction of energy system development. Integrated Energy System (IES) breaks through technical, market and management barriers of traditional energy systems, and it makes unified planning and scheduling for electricity, gas, heat, cold, etc. However, IES contains a variety of energy forms, and those energy forms are coupled with each other. Its planning and operation are challenging problems. Therefore, this paper proposes an IES planning model, which comprehensively considers optimization of the equipment configuration, interconnection of multiple energy stations, renewable energy integration, and optimal operation strategy. During the planning decision-making, planners can use this model to analyze and evaluate the impact of various factors on the planning indicators. Using the proposed model, an IES composed of several buildings in a street block is planned in detail and the effectiveness of the proposed planning model and its solution method is proved. The case study results show the total cost and carbon emission of the model considering both energy station interconnection and RES integration are reduced by 20.2% and 41.5%.

关键词： Carbon emission energy bus model integrated energy system planning mixed integer linear programming multiple energy station interconnection renewable energy integration

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Rolling stock rescheduling in high-speed railway networks via a nested Benders decomposition approach

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2025年 171卷

作者： Li, Denghui Zhao, Jun Peng, Qiyuan Wang, Dian Zhong, Qingwei Southwest Jiaotong Univ Sch Transportat & Logist Chengdu 611756 Sichuan Peoples R China Southwest Jiaotong Univ Natl United Engn Lab Integrated & Intelligent Tran Chengdu 611756 Sichuan Peoples R China Hefei Univ Technol Sch Automot & Transportat Engn Hefei 230009 Anhui Peoples R China Civil Aviat Flight Univ China Coll Air Traff Management Guanghan 618307 Sichuan Peoples R China

This paper addresses a rolling stock rescheduling problem (RSRP) during disruptions in a high-speed railway network, focusing on decisions related to the reassignment of physical rolling stock units to trips, deadheading schedules, and maintenance plans and schedules, while taking into account deadheading trips and maintenance requirements. A mixed integer linear programming (MILP) model is formulated, leveraging a directed acyclic graph to represent all feasible connections for each rolling stock unit. The objective is to minimize the weighted sum of canceled trips, schedule deviations, and various service quality and cost indicators. An exact nested Benders decomposition (NBD) algorithm is developed to solve this model. In the algorithm, the RSRP is first decomposed into an outer integer master problem (OMP) and an outer integer subproblem (OSP). The OMP is then divided into an inner integer master problem (IMP) and an inner integer subproblem (ISP), and is solved using the logic-based Benders decomposition (LBBD) algorithm, where strengthened feasibility cuts and optimality cuts, as well as valid inequalities, are added to the IMP to enhance the algorithm's performance. The OSP, a feasibility problem, is further decomposed into many easier problems at each depot. Subsequently, three implementations including two branch-and-check type approaches and one LBBD approach are customized to solve the outer decomposition problem. We also propose a three-stage approach to solve the IMP, ISP, and OSP, sequentially. The approaches are tested on a set of instances constructed from the high-speed railway network in China. The results show that the approaches can quickly find (near-)optimal solutions for tested instances within a short computation time of several minutes, making it suitable for real-time rolling stock rescheduling applications.

关键词： High-speed railway transportation Rolling stock rescheduling Deadheading mixed integer linear programming Nested Benders decomposition

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Seniority-based surgery scheduling and team assignment

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SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES 2025年第2期50卷 1-8页

作者： Didem Batur Sir, G. Oner, Nurhan Erol, Serpil Gazi Univ Fac Engn Dept Ind Engn Ankara Turkiye Gen Directorate PTT Ankara Turkiye

Crucial resources for surgical operations are obviously operating rooms and surgical teams. It is essential to ensure the equitable assignment of operations to both operating rooms and surgical teams, taking into account the capacities, resting periods, and cleaning times. Additionally, the varying levels of expertise required for different types of surgeries should be considered. In this study, we focus on these challenges within the context of surgery scheduling and team assignment problems. We propose a mathematical model-based solution approach for operating room planning that aligns surgical teams with the specific requirements of various procedures, consistent with real life applications. Key considerations include appropriate workload distribution, sufficient rest times, and opportunities for surgeon training. By utilizing the methodology presented in this study, we effectively assign daily planned operations to the appropriate operating rooms and surgical teams. The proposed procedure is successfully applied to real data from the otorhinolaryngology department of a public hospital, as well as to randomly generated test problems. This study provides exact solutions for the aforementioned surgery scheduling and team assignment issues.

关键词： Operating room scheduling surgical team assignment surgery types surgeon seniority mixed integer linear programming

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