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33rd International Conference on Automated Planning and Scheduling, ICAPS 2023

作者： Horn, Matthias Demirovic, Emir Yorke-Smith, Neil Algorithmics Group Delft University of Technology Netherlands

ISBN: (纸本)1577358813

We solve a challenging scheduling problem with parallel batch processing and two-dimensional shelf strip packing constraints that arises in the tool coating field. Tools are assembled on so-called planetaries (batches) before they are loaded into coating machines to get coated. The assembling is not trivial and must fulfil specific constraints, which we refer to as shelf strip packing constraints. Further, each tool is associated with a starting time window s.t. tools can only be put on the same planetary if their time window overlap. The objective is to minimise the makespan and the number of required planetaries. Since the problem naturally decomposes into scheduling and packing parts, we tackle the problem with a two-phase logic-based Benders decomposition approach. The master problem assigns items to batches. The first phase solves as subproblem the packing problem by checking if the assignment is feasible, whereas the second phase solves the scheduling subproblem. The approach is compared with a monolithic mixed integer linear programming approach as well as a monolithic constraint programming approach. Experimental evaluation shows that our proposed approach outperforms the state-of-the-art benchmarks by solving more instances to optimality in a shorter time. Copyright © 2023, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： constraint programming

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Multi-objective Optimization for the Design of Salary Structures 20th

Multi-objective Optimization for the Design of Salary Struct...

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20th International Conference on the Integration of constraint programming, Artificial Intelligence, and Operations Research (CPAIOR)

作者： Tremblay, Francois-Alexandre Piche-Meunier, Dominique Dubois, Louis Univ Laval Dept Comp Sci & Software Engn Quebec City PQ Canada

ISBN: (纸本)9783031332708;9783031332715

In a context of labor shortage and strong global competition for talent, salary management is becoming a critical issue for companies wishing to attract, engage and retain qualified employees. This paper presents a multi-objective optimization model to balance the internal equity, external equity and costs trade-offs associated with the design of salary structures. Solutions are generated to estimate and explore the Pareto frontier using real compensation data from a unionized establishment in the public sector. Our work shows the interest of using combinatorial optimization techniques in the design of salary structures.

关键词： Multi-objective optimization constraint programming salary structure decision support system

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Parsimonious Clone Tree Integration in cancer

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ALGORITHMS FOR MOLECULAR BIOLOGY 2022年第1期17卷 1-14页

作者： Sashittal, Palash Zaccaria, Simone El-Kebir, Mohammed Univ Illinois Dept Comp Sci Urbana IL 61801 USA UCL Computat Canc Genom Res Grp Canc Inst London England UCL Canc Res UK Lung Canc Ctr Excellence Canc Inst London England Univ Illinois Canc Ctr Illinois Urbana IL 61801 USA

Background Every tumor is composed of heterogeneous clones, each corresponding to a distinct subpopulation of cells that accumulated different types of somatic mutations, ranging from single-nucleotide variants (SNVs) to copy-number aberrations (CNAs). As the analysis of this intra-tumor heterogeneity has important clinical applications, several computational methods have been introduced to identify clones from DNA sequencing data. However, due to technological and methodological limitations, current analyses are restricted to identifying tumor clones only based on either SNVs or CNAs, preventing a comprehensive characterization of a tumor's clonal composition. Results To overcome these challenges, we formulate the identification of clones in terms of both SNVs and CNAs as a integration problem while accounting for uncertainty in the input SNV and CNA proportions. We thus characterize the computational complexity of this problem and we introduce PACTION (PArsimonious Clone Tree integratION), an algorithm that solves the problem using a mixed integer linear programming formulation. On simulated data, we show that tumor clones can be identified reliably, especially when further taking into account the ancestral relationships that can be inferred from the input SNVs and CNAs. On 49 tumor samples from 10 prostate cancer patients, our integration approach provides a higher resolution view of tumor evolution than previous studies. Conclusion PACTION is an accurate and fast method that reconstructs clonal architecture of cancer tumors by integrating SNV and CNA clones inferred using existing methods.

关键词： Intra-tumor heterogeneity Perfect phylogeny constraint programming Single-cell DNA sequencing Perfect phylogeny

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Towards the automatic and optimal selection of risk treatments for business processes using a constraint programming approach

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INFORMATION AND SOFTWARE TECHNOLOGY 2013年第11期55卷 1948-1973页

作者： Jesus Varela-Vaca, Angel Gasca, Rafael M. Univ Seville ETS Ingn Informat Dept Comp Languages & Syst Seville 41012 Spain

Context: The use of Business Process Management Systems (BPMS) has emerged in the IT arena for the automation of business processes. In the majority of cases, the issue of security is overlooked by default in these systems, and hence the potential cost and consequences of the materialization of threats could produce catastrophic loss for organizations. Therefore, the early selection of security controls that mitigate risks is a real and important necessity. Nevertheless, there exists an enormous range of IT security controls and their configuration is a human, manual, time-consuming and error-prone task. Furthermore, configurations are carried out separately from the organization perspective and involve many security stakeholders. This separation makes difficult to ensure the effectiveness of the configuration with regard to organizational requirements. Objective: In this paper, we strive to provide security stakeholders with automated tools for the optimal selection of IT security configurations in accordance with a range of business process scenarios and organizational multi-criteria. Method: An approach based on feature model analysis and constraint programming techniques is presented, which enable the automated analysis and selection of optimal security configurations. Results: A catalogue of feature models is determined by analyzing typical IT security controls for BPMSs for the enforcement of the standard goals of security: integrity, confidentiality, availability, authorization, and authentication. These feature models have been implemented through constraint programs, and constraint programming techniques based on optimized and non-optimized searches are used to automate the selection and generation of configurations. In order to compare the results of the determination of configuration a comparative analysis is given. Conclusion: In this paper, we present innovative tools based on feature models, constraint programming and multi-objective techniques that en

关键词： Business process Business process management systems Security Risk treatments constraint programming Feature model

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A Finite-Domain constraint-Based Approach on the Stockyard Planning Problem 34th

A Finite-Domain Constraint-Based Approach on the Stockyard P...

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34th International Conference on Database and Expert Systems Applications (DEXA)

作者： Loeffler, Sven Becker, Ilja Hofstedt, Petra Brandenburg Univ Technol Cottbus Senftenberg Konrad Wachsmann Allee 5 Cottbus Germany

ISBN: (纸本)9783031398209;9783031398216

Transport problems are a significant challenge for companies, i.e. due to concerns about climate change and the constant increase in raw material prices, such as for petrol. One issue in transporting bulk materials is the Stockyard Planning Problem (SPP), which plays a crucial role in mine production scheduling and bulk material transportation by using stockpiles to store and blend raw material. The SPP aims to: 1) blend superior and inferior components to achieve a desired quality, 2) transfer material from import (e.g. ocean-going ships) to interim storage (e.g. stockpiles) and then to export (e.g. docks at inland ports), and 3) find a time-/cost-optimized schedule for working steps of 1 and 2. This paper presents a novel constraint-based approach for solving the Stockyard Planning Problem (SPP) by utilizing new abstractions such as time, storage, and potential movements within a stockyard system.

关键词： Planning and Scheduling Decision Support Systems Mining Stockyard Planning Problem SPP constraint programming

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Aerial Vehicle Routing and Scheduling for UAS Traffic Management: A Hybrid Monte Carlo Tree Search Approach 42

Aerial Vehicle Routing and Scheduling for UAS Traffic Manage...

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IEEE/AIAA 42nd Digital Avionics Systems Conference (DASC)

作者： Chour, Kenny Pradeep, Priyank Munishkin, Alexey A. Kalyanam, Krishna M. NASA Ames Res Ctr Metis Technol Solut Moffett Field CA 94035 USA NASA Ames Res Ctr USRA Moffett Field CA 94035 USA NASA Ames Res Ctr Aviat Syst Div Moffett Field CA 94035 USA

ISBN: (纸本)9798350333572

We present the Multi-Route Weighted Package Delivery Problem (MRWPDP) and a scalable solution methodology as a major step towards enabling an airspace deconfliction service for drone delivery operations. The problem is motivated by Strategic deconfliction under the FAA's "Unmanned Aircraft Systems Traffic Management" Concept of Operations. MRWPDP falls under a class of vehicle routing and scheduling problems, and as such is NP-Hard. In MRWPDP, a graph network is given which consists of depots, drop-off sites, and multiple routes connecting the two. In addition, routes are weighted by the associated ground risk and total travel distance for package delivery. The goal is to optimally schedule the departure time and assign routes to a known set of vehicles at the depot. We propose a heuristic solution to the problem by borrowing techniques from Mixed Integer Linear programming (MILP), constraint programming, and Monte Carlo Tree Search (MCTS). The resulting hybrid framework is MCTS with Bound-and-Prune (BP) and rapid simulated updates (U), or MCTS-BP-U. This approach is able to quickly provide a feasible solution for MRWPDP, even for large problem instances up to 1000 vehicles. We provide a MILP formulation of MRWPDP and compare its performance against MCTS-BP-U in terms of solution quality. An agent-based model simulation is conducted as a final step to validate the efficacy of our approach.

关键词： Monte Carlo Tree Search Mixed Integer programming constraint programming Combinatorial Optimization Scheduling and Routing

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Binary Search-Based Methods for Solving constraint Hierarchies over Finite Domains 35

Binary Search-Based Methods for Solving Constraint Hierarchi...

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35th IEEE International Conference on Tools with Artificial Intelligence (ICTAI)

作者： Hosobe, Hiroshi Satoh, Ken Hosei Univ Fac Comp & Informat Sci Tokyo Japan Natl Inst Informat Principles Informat Res Div Tokyo Japan

ISBN: (纸本)9798350342734

constraint programming is a powerful tool for modeling and solving various problems. Especially, soft constraints are useful since they enable the treatment of over- and under-constrained real-world problems by relaxing conflicting constraints and introducing default constraints. constraint hierarchies provide a soft constraint framework that introduces hierarchical preferences called strengths. In a constraint hierarchy, constraints are associated with strengths such as required, strong, medium, and weak, and a solution is obtained to maximally satisfy stronger constraints in the sense of a given solution criterion. In this paper, we propose three methods based on binary search for solving constraint hierarchies over finite domains by using a criterion called unsatisfied-count-better. Our methods solve constraint hierarchies by encoding them into ordinary constraint satisfaction problems and repeatedly solving the encoded problems with an external solver. We also present the implementations of our methods and the results of the experiment that we conducted to evaluate them.

关键词： constraint programming constraint solver soft constraint constraint hierarchy

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Measures of balance in combinatorial optimization

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4OR-A QUARTERLY JOURNAL OF OPERATIONS RESEARCH 2022年第3期20卷 391-415页

作者： Olivier, Philippe Lodi, Andrea Pesant, Gilles Polytech Montreal Montreal PQ Canada Canada Excellence Res Chair Montreal PQ Canada

The concept of balance plays an important role in many combinatorial optimization problems. Yet there exist various ways of expressing balance, and it is not always obvious how best to achieve it. In this methodology-focused paper, we study three cases where its integration is deficient and analyze the causes of these inadequacies. We examine the characteristics and performance of the measures of balance used in these cases, and provide general guidelines regarding the choice of a measure.

关键词： Balance Fairness constraint programming Integer programming

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Multi-objective Finite-Domain constraint-Based Forest Management 22nd

Multi-objective Finite-Domain Constraint-Based Forest Manage...

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22nd Regular meeting of the Portuguese-Association-of-Operational-Research (APDIO)

作者： Eloy, Eduardo Bushenkov, Vladimir Abreu, Salvador Univ Evora Evora Portugal Univ Evora CIMA Evora Portugal Univ Evora NOVA LINCS Evora Portugal

ISBN: (纸本)9783031464393;9783031464386

This paper describes an implementation of a constraint programming approach to the problem of multi-criteria forest management optimization. The goal is to decide when to harvest each forest unit while striving to optimize several criteria under spatial restrictions. With a large number of management units, the optimization problem becomes computationally intractable. We propose an approach for deriving a set of efficient solutions for the entire region. The proposed methodology was tested for Vale do Sousa region in the North of Portugal.

关键词： Forest management constraint programming constraint modeling Multi-criteria optimization Pareto frontier

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Securing Optimized Code Against Power Side Channels 36

Securing Optimized Code Against Power Side Channels

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IEEE 36th Computer Security Foundations Symposium (CSF)

作者： Tsoupidi, Rodothea Myrsini Lozano, Roberto Casta Neda Troubitsyna, Elena Papadimitratos, Panagiotis Royal Inst Technol KTH Stockholm Sweden

ISBN: (纸本)9798350321920

Side-channel attacks impose a serious threat to cryptographic algorithms, including widely employed ones, such as AES and RSA. These attacks take advantage of the algorithm implementation in hardware or software to extract secret information via side channels. Software masking is a mitigation approach against power side-channel attacks aiming at hiding the secret-revealing dependencies from the power footprint of a vulnerable implementation. However, this type of software mitigation often depends on general-purpose compilers, which do not preserve non-functional properties. Moreover, microarchitectural features, such as the memory bus and register reuse, may also leak secret information. These abstractions are not visible at the high-level implementation of the program. Instead, they are decided at compile time. To remedy these problems, security engineers often sacrifice code efficiency by turning off compiler optimization and/or performing local, post-compilation transformations. This paper proposes Secure by Construction Code Generation (SecCG), a constraint-based compiler approach that generates optimized yet protected against power side channels code. SecCG controls the quality of the mitigated program by efficiently searching the best possible low-level implementation according to a processor cost model. In our experiments with twelve masked cryptographic functions up to 100 lines of code on Mips32 and ARM Thumb, SecCG speeds up the generated code from 77% to 6.6 times compared to non-optimized secure code with an overhead of up to 13% compared to non-secure optimized code at the expense of a high compilation cost. For security and compiler researchers, this paper proposes a formal model to generate power side channel free low-level code. For software engineers, SecCG provides a practical approach to optimize performance critical and vulnerable cryptographic implementations that preserve security properties against power side channels.

关键词： compilation power side-channel attacks code optimization software masking constraint programming

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