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integer linear programming for unsupervised training set selection in molecular machine learning

MACHINE LEARNING-SCIENCE AND TECHNOLOGY 2025年第2期6卷

作者： Haeberle, Matthieu van Gerwen, Puck Laplaza, Ruben Briling, Ksenia R. Weinreich, Jan Eisenbrand, Friedrich Corminboeuf, Clemence Ecole Polytech Fed Lausanne Inst Chem Sci & Engn Lab Computat Mol Design CH-1015 Lausanne Switzerland Ecole Polytech Fed Lausanne Chair Discrete Optimizat CH-1015 Lausanne Switzerland Natl Ctr Competence Res Catalysis NCCR Catalysis Zurich Switzerland

integer linear programming (ILP) is an elegant approach to solve linear optimization problems, naturally described using integer decision variables. Within the context of physics-inspired machine learning (ML) applied to chemistry, we demonstrate the relevance of an ILP formulation to select molecular training sets for predictions of size-extensive properties. We show that our algorithm outperforms existing unsupervised training set selection approaches, especially when predicting properties of molecules larger than those present in the training set. We argue that the reason for the improved performance is due to the selection that is based on the notion of local similarity (i.e. per-atom) and a unique ILP approach that finds optimal solutions efficiently. Altogether, this work provides a practical algorithm to improve the performance of physics-inspired ML models and offers insights into the conceptual differences with existing training set selection approaches.

关键词： integer linear programming molecular machine learning quantum chemistry training set selection

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integer linear programming-Based Simultaneous Scheduling and Binding for SiLago Framework

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IEEE ACCESS 2024年 12卷 124081-124094页

作者： Pudi, Dhilleswararao Malviya, Shivam Boppu, Srinivas Yang, Yu Hemani, Ahmed Cenkeramaddi, Linga Reddy Indian Inst Technol Bhubaneswar Sch Elect Sci Bhubaneswar 752050 India KTH Royal Inst Technol Div Elect & Embedded Syst Stockholm S-11428 Sweden Univ Agder Dept ICT N-4630 Grimstad Norway

Coarse-Grained Reconfigurable Array (CGRA) architectures are potential high-performance and power-efficient platforms. However, mapping applications efficiently on CGRA, which includes scheduling and binding operations on functional units and variables on registers, is a daunting problem. SiLago is a recently developed VLSI design framework comprising two large-scale reconfigurable fabrics: Dynamically Reconfigurable Resource Array (DRRA) and Distributed Memory Architecture (DiMArch). It uses the Vesyla compiler to map applications on these fabrics. The present version of Vesyla executes binding and scheduling sequentially, with binding first, followed by scheduling. In this paper, we proposed an integer linear programming (ILP)-based exact method to solve scheduling and binding simultaneously that delivers better solutions while mapping applications on these fabrics. The proposed ILP combines two objective functions, one for scheduling and one for binding, and both of these objective functions are coupled with weightage factors $\alpha $ and $\beta $ so that the user can have the flexibility to prioritize either scheduling or binding or both based on the requirements. We determined the binding and execution time of image processing tasks and various routines of the Basic linear Algebraic Subprogram (BLAS) using the proposed ILP for multiple combinations of weightage factors. Furthermore, a comparison analysis has been conducted to compare the latency and power dissipation of several benchmarks between the existing and proposed approaches. The experimental results demonstrate that the proposed method exhibits a substantial reduction in power consumption and latency compared to the existing method.

关键词： Random access memory Radio frequency Registers Switches Dynamic scheduling Reconfigurable architectures Distributed management Memory management integer linear programming Scheduling Power demand Coarse-grain reconfigurable architecture dynamically reconfigurable resource array distributed memory architecture integer linear programming high-level synthesis scheduling binding

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Decision support system for tower crane location and material supply point in construction sites using an integer linear programming model

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ENGINEERING CONSTRUCTION AND ARCHITECTURAL MANAGEMENT 2023年第4期30卷 1444-1462页

作者： Amiri, Roya Sardroud, Javad Majrouhi Kermani, Vahid Momenaei Islamic Azad Univ Fac Civil & Earth Resources Engn Dept Civil Engn Cent Tehran Branch Tehran Iran Islamic Azad Univ Dept Math Kerman Branch Kerman Iran

Purpose The site layout has a significant impact on the efficiency of construction operations. Planning an effective site layout partly involves identifying and positioning temporary facilities such as tower cranes and areas on the jobsite for materials storage. This study proposes an approach to optimizing the type and location of the tower crane and material supply point on construction sites. Design/methodology/approach The problem is formulated into an integer linear programming (ILP) model considering the total cost of material transportation as the objective function and site conditions as constraints. The efficacy of the approach is demonstrated by finding the optimum site layout for a numerical example. The proposed model is validated and verified using two methods. Findings Results indicate that the proposed model successfully identifies the type and location of the tower crane and the location of material supply point, leading to approximately 20% cost reduction compared with when such features of a site layout are decided solely based on experience and educated guesses of the construction manager. Originality/value The primary contribution of this study is to present a modified linear mathematical model for site layout optimization that exhibits improved performance compared with previous models. The type and location of the tower crane and the material supply point as decision variables are extracted directly from solving the proposed model. The proposed model will help enhance time and cost efficiency on construction sites.

关键词： Decision making Tower crane Material supply point Optimization integer linear programming Construction site

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integer linear programming formulations for double roman domination problem

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OPTIMIZATION METHODS & SOFTWARE 2022年第1期37卷 1-22页

作者： Cai, Qingqiong Fan, Neng Shi, Yongtang Yao, Shunyu Nankai Univ Coll Comp Sci Tianjin Peoples R China Univ Arizona Dept Syst & Ind Engn Tucson AZ 85721 USA Nankai Univ Ctr Combinator Tianjin Peoples R China Nankai Univ LPMC Tianjin Peoples R China

For a graph , a double Roman dominating function (DRDF) is a function having the property that if , then vertex v must have at least two neighbours assigned 2 under f or at least one neighbour u with , and if , then vertex v must have at least one neighbour u with . In this paper, we consider the double Roman domination problem, which is an optimization problem of finding the DRDF f such that is minimum. We propose five integer linear programming (ILP) formulations and one mixed integer linear programming formulation with polynomial number of constraints for this problem. Some additional valid inequalities and bounds are also proposed for some of these formulations. Further, we prove that the first four models indeed solve the double Roman domination problem, and the last two models are equivalent to the others regardless of the variable relaxation or usage of a smaller number of constraints and variables. Additionally, we use one ILP formulation to give an -approximation algorithm. All proposed formulations and approximation algorithm are evaluated on randomly generated graphs to compare the performance.

关键词： Double roman domination integer linear programming approximation algorithm 90C10 68W25

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integer linear programming Based Design of Deadlock-Free Routing for Chiplet-Based Systems 37

Integer Linear Programming Based Design of Deadlock-Free Rou...

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37th IEEE International System-on-Chip Conference, SOCC 2024

作者： Liu, Shuang Radetzki, Martin University of Stuttgart Embedded Systems Institute of Computer Architecture and Computer Engineering Stuttgart Germany

ISBN: (纸本)9798350377569

Chiplet-based systems have become prominent in large Systems-on-Chips (SoCs) as a means to mitigate increasing design costs. However, the integration of multiple chiplets introduces new challenges in the interconnection network, potentially leading to deadlocks. In this paper, we propose an integer linear programming (ILP) based design approach to address this issue. Our method considers various design factors for deadlock-free routing, such as topology, latency, load balancing, path diversity, and fault tolerance, applicable to both general-purpose chiplets and application-specific chiplets. It facilitates the determination of optimal turn restrictions for general-purpose chiplets or constructs optimal deadlock-free routing paths for application-specific chiplets if the communication patterns are known. The results demonstrate the capability of the method to find optimal solutions under various design considerations. © 2024 IEEE.

关键词： integer linear programming

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Fault Diagnosis of Labeled Petri Nets Under Attacks Using integer linear programming

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2025年 22卷 11881-11893页

作者： Li, Tengbo Ren, Huorong Liu, Ruotian Pia Fanti, Maria Li, Zhiwu Xidian Univ Sch Mechanoelect Engn Xian 710071 Peoples R China Polytech Univ Bari Dept Elect & Informat Engn I-70125 Bari Italy Macau Univ Sci & Technol Inst Syst Engn Macau Peoples R China

This paper deals with the online fault diagnosis problem of discrete event systems under malicious external attacks. We consider a scenario where an attacker can intercept certain sensor measurements and alter them arbitrarily, potentially causing a diagnoser to malfunction. In the framework of labeled Petri nets, a novel integer linear programming problem is formulated by introducing binary variables to estimate the possible transition sequences of an observation that may have been tampered with by an attacker. The proposed approach makes two main contributions. The first one is that, by specifying two different objective functions to the integer linear programming problem, we can obtain the diagnosis results in the presence of attacks, which classic diagnosers may fail to achieve;the second is computational efficiency. In the absence of attacks, the proposed approach is experimentally verified to have lower computational overhead compared with the existing results that are based on integer linear programming and those using basis markings. Finally, the proposed approach is illustrated through a manufacturing system for assembling brake valves.

关键词： Fault diagnosis Petri nets integer linear programming Discrete-event systems State estimation Manufacturing systems linear programming Computational modeling Computational efficiency Communication channels Cyber attack discrete event system fault diagnosis integer linear programming labeled Petri net

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State-Based Fault Diagnosis of Finite-State Vector Discrete-Event Systems via integer linear programming

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SENSORS 2025年第5期25卷 1452-1452页

作者： Chen, Qinrui Garayev, Mubariz Liu, Ding Xidian Univ Sch Electromech Engn Xian 710071 Peoples R China King Saud Univ Coll Sci Dept Math POB 2455 Riyadh Saudi Arabia

This paper presents a state-based method to address the verification of K-diagnosability and fault diagnosis of a finite-state vector discrete-event system (Vector DES) with partially observable state outputs due to limited sensors. Vector DES models consist of an arithmetic additive structure in both the state space and state transition function. This work offers a necessary and sufficient condition for verifying the K-diagnosability of a finite-state Vector DES based on state sensor outputs, employing integer linear programming and the mathematical representation of a Vector DES. Predicates are employed to diagnose faults in a Vector DES online. Specifically, we use three different kinds of predicates to divide system state outputs into different subsets, and the fault occurrence in a system is detected by checking a subset of outputs. Online diagnosis is achieved via solving integer linear programming problems. The conclusions obtained in this work are explained by means of several examples.

关键词： vector discrete-event system fault diagnosis K-diagnosability predicate integer linear programming

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An integer linear programming model for the label printing problem

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2025年第1期32卷 270-288页

作者： Xu, Dehua Shen, Yuan Cao, Yu Xu, Limin Yang, Fengzhao Xie, Yunzhou Nanjing Univ Finance & Econ Sch Int Econ & Business Nanjing 210023 Peoples R China Nanjing Univ Finance & Econ Sch Appl Math Nanjing 210023 Peoples R China Imperial Coll London Fac Nat Sci London SW7 2AZ England

In a recent paper published in this journal, Alonso-Pecina et al. collect several sets of benchmark instances for the label printing problem from the literature and they also propose their own instances. Due to the intractability of the problem, no optimal solutions were declared for most of these instances. In this paper, we propose an integer linear programming model for the problem. We obtain optimal solutions or show that the solutions provided in the literature are already optimal for most of these instances based on the model. For some of the rest instances, we provide better solutions compared to the previous best solutions in the literature.

关键词： label printing benchmark instances optimal solutions integer linear programming

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IntSat: integer linear programming by conflict-driven constraint learning

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OPTIMIZATION METHODS & SOFTWARE 2024年第1期40卷 169-196页

作者： Nieuwenhuis, Robert Oliveras, Albert Rodriguez-Carbonell, Enric Univ Politecn Cataluna Dept Comp Sci Barcelona Spain

State-of-the-art SAT solvers are nowadays able to handle huge real-world instances. The key to this success is the Conflict-Driven Clause-Learning (CDCL) scheme, which encompasses a number of techniques that exploit the conflicts that are encountered during the search for a solution. In this article, we extend these techniques to integer linear programming (ILP), where variables may take general integer values instead of purely binary ones, constraints are more expressive than just propositional clauses, and there may be an objective function to optimize. We explain how these methods can be implemented efficiently and discuss possible improvements. Our work is backed with a basic implementation showing that, even in this far less mature stage, our techniques are already a useful complement to the state of the art in ILP.

关键词： integer linear programming SAT solving conflict-driven clause learning

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Finding a second Hamiltonian decomposition of a 4-regular multigraph by integer linear programming

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JOURNAL OF COMBINATORIAL OPTIMIZATION 2024年第5期47卷 89-89页

作者： Nikolaev, Andrei V. Klimov, Egor V. PG Demidov Yaroslavl State Univ Yaroslavl Russia

A Hamiltonian decomposition of a regular graph is a partition of its edge set into Hamiltonian cycles. We consider the second Hamiltonian decomposition problem: for a 4-regular multigraph, find 2 edge-disjoint Hamiltonian cycles different from the given ones. This problem arises in polyhedral combinatorics as a sufficient condition for non-adjacency in the 1-skeleton of the traveling salesperson polytope. We introduce two integer linear programming models for the problem based on the classical Dantzig-Fulkerson-Johnson and Miller-Tucker-Zemlin formulations for the traveling salesperson problem. To enhance the performance on feasible problems, we supplement the algorithm with a variable neighborhood descent heuristic w.r.t. two neighborhood structures and a chain edge fixing procedure. Based on the computational experiments, the Dantzig-Fulkerson-Johnson formulation showed the best results on directed multigraphs, while on undirected multigraphs, the variable neighborhood descent heuristic was especially effective.

关键词： Hamiltonian decomposition Traveling salesperson polytope 1-skeleton integer linear programming Dantzig-Fulkerson-Johnson formulation Miller-Tucker-Zemlin formulation Subtour elimination constraints Edge-disjoint 2-factors Local search Variable neighborhood descent Chain edge fixing

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