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2nd Genetic and Evolutionary Computation Conference (GECCO)

作者： Szczepanski, Nicolas Audemard, Gilles Jourdan, Laetitia Lecoutre, Christophe Mousin, Lucien Veerapen, Nadarajen Univ Lille CNRS Cent Lille UMR 9189CRIStAL F-59000 Lille France Univ Artois CRIL CNRS UMR 8188 Lens France Lille Catholic Univ Fac Gest Econ & Sci Lille France

ISBN: (纸本)9781450383509

In the domain of partial classification, recent studies about multi-objective local search (MOLS) have led to new algorithms offering high performance, particularly when the data are imbalanced. In the presence of such data, the class distribution is highly skewed and the user is often interested in the least frequent class. Making further improvements certainly requires exploiting complementary solving techniques (notably, for the rule mining problem). As constraint programming (CP) has been shown to be effective on various combinatorial problems, it is one such promising complementary approach. In this paper, we propose a new hybrid combination, based on MOLS and CP that are quite orthogonal. Indeed, CP is a complete approach based on powerful filtering techniques whereas MOLS is an incomplete approach based on Pareto dominance. Experimental results on real imbalanced datasets show that our hybrid approach is statistically more efficient than a simple MOLS algorithm on both training and tests instances, in particular, on partial classification problems containing many attributes.

关键词： Partial Classification Imbalanced Data Multi-objective Optimization Local Search constraint programming

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Short-Term Scheduling of Production Fleets in Underground Mines Using CP-Based LNS 18th

Short-Term Scheduling of Production Fleets in Underground Mi...

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18th International Conference on the Integration of constraint programming, Artificial Intelligence, and Operations Research (CPAIOR)

作者： Astrand, Max Johansson, Mikael Feyzmahdavian, Hamid Reza KTH Royal Inst Technol Sch Elect Engn & Comp Sci Div Decis & Control Syst Stockholm Sweden ABB Corp Res Vasteras Sweden

ISBN: (纸本)9783030782306;9783030782290

Coordinating the mobile production fleet in underground mines becomes increasingly important as the machines are more and more automated. We present a scheduling approach that applies to several of the most important production methods used in underground mines. Our algorithm combines constraint programming with a large neighborhood search strategy that dynamically adjusts the neighborhood size. The resulting algorithm is complete and able to rapidly improve constructed schedules in practice. In addition, it has important benefits when it comes to the acceptance of the approach in real-life operations. Our approach is evaluated on public and private industrial problem instances representing different mines and production methods. We find significant improvements over the current industrial practice.

关键词： Scheduling Underground mining constraint programming Large neighborhood search

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Agile and Autonomous Production Control for Remanufacturing 9

Agile and Autonomous Production Control for Remanufacturing

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9th International Conference on Control, Mechatronics and Automation (ICCMA)

作者： Gros, Sebastian Gerke, Wolfgang Plapper, Peter Vette-Steinkamp, Matthias Trier Univ Appl Sci Sustainable Prod Proc & Ind Robot Environm Campus Birkenfeld Birkenfeld Germany Univ Luxembourg Dept Engn Luxembourg Luxembourg

ISBN: (纸本)9781665410731

Motivated by high ecological and economical potentials, remanufacturing is receiving increasing attention as a process that puts used products into an "as-good-as-new-or-better" condition. Here, many challenges occur, which are unseen in manufacturing, resulting from unknown conditions of used products. One example is the stochastic routing of the products through the remanufacturing system (RS), which makes a flexible material transport by e.g. automated guided vehicles (AGVs) necessary. This places special demands on the control of the RS. To handle these uncertainties a decentralized-hierarchical control architecture is presented. The scheduling of machines and AGVs is optimized simultaneously using constraint programming (CP). All the participants within the RS will be networked as a cyber-physical system and controlled by decentralized components. The approach is validated through simulation and the implementation in a model factory. Results show a 35.6% makespan reduction, short computing times and the ability to react adequately to unforeseen events.

关键词： simultaneous scheduling AGV constraint programming remanufacturing production control

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Shelf placement optimization for air products

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JOURNAL OF REVENUE AND PRICING MANAGEMENT 2021年第3期20卷 322-329页

作者： Szymanski, Tomasz Darrow, Ross Ul Spacerowa 23 PL-33190 Ciezkowice Poland 3917 Cedar Ridge Dr Bedford TX 76021 USA Sabre Res Southlake TX USA

Airlines are increasingly trying to differentiate their offers, so one airline's bare bones low fare may, for some travelers, be equivalent to another airline's high fare, if the low fare bundles some ancillaries a traveler wants. Because of differentiation of airline offers the air traveler must simultaneously compare air fares and the ancillaries included. Price comparison is also difficult as the same cabin offers vary by the ancillaries included across the competing airlines. We are proposing a shelf product assortment method for categorizing airline offers into utility levels, thus facilitating the choice task of air travelers. We describe possible known approaches, describe Sabre's proposal, provide information on the optimization methods used, and propose future work in the field.

关键词： Offer optimization Airlines offer management Bundles Electronic retail Shelf space product assortment constraint programming

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Energy-efficient automated vertical farms

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2022年 109卷 102611-102611页

作者： Delorme, Maxence Santini, Alberto Tilburg Univ Dept Econometr & Operat Res Tilburg Netherlands Univ Pompeu Fabra Dept Econ & Business Barcelona Spain ESSEC Business Sch Cergy France Paris Cergy Univ Inst Adv Studies Cergy France

Autonomous vertical farms (VFs) are becoming increasingly more popular because they allow to grow food minimising water consumption and the use of pesticides, while greatly increasing the yield per square metre compared with traditional agriculture. To meet sustainability goals, however, VFs must operate at maximum efficiency;it would be otherwise impossible to compete with the energy source pow-ering plant growth in traditional agriculture: the sun. We introduce the Vertical Farming Elevator Energy Minimisation Problem ( VFEEMP ), which arises when minimising the energy consumption of automatic elevators servicing VFs. We prove that the decision problem associated with the VFEEMP is N P-complete. To solve the problem, we propose three Mixed-Integer Linear programming (MIP) formulations together with valid inequalities, and a constraint programming model. We present a large set of instances, both synthetic and derived from real-life data, and we determine through extensive computational experiments which instance characteristics have an impact on the difficulty of the problem and which formulations are the most suitable to solve the VFEEMP. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license ( http://***/licenses/by/4.0/ )

关键词： Vertical farming Task scheduling Operational research applications Integer linear programming constraint programming

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A constraint-based Approach for Enumerating Gradual Itemsets 33

A Constraint-based Approach for Enumerating Gradual Itemsets

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IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI)

作者： Hidouri, Amel Jabbour, Said Lonlac, Jerry Raddaoui, Badran Univ dArtois CRIL CNRS Lens France Univ Lille IMT Nord Europe Inst Mines Telecom Ctr Digital Syst F-59000 Lille France IP Paris Telecom SudParis SAMOVAR Paris France

ISBN: (纸本)9781665408981

Gradual itemsets model complex attributes covariations of the form the more or less is A, the more or less is B. Recently, such kind of itemsets has received great attention over the last years, and several proposals have been introduced to automatically extract these patterns from numerical databases. Unfortunately, discovering such itemsets remains challenging because of the exponential combinatorial search space. In this paper, we first formalize the problem of mining gradual itemsets as a constraint-based problem. Then, we use SAT solvers for solving the corresponding propositional satisfiability problem. Extensive experiments on real-world datasets confirm that our proposal is competitive with GRITE, one of the most efficient state-of-the-art algorithm for discovering frequent gradual itemsets. Lastly, we show the flexibility of our SAT-based approach by its ability to modeling additional user constraints without revising the solving process.

关键词： Data Mining Gradual itemsets constraint programming Propositional satisfiability problem

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CONJURE: Automatic Generation of constraint Models from Problem Specifications

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ARTIFICIAL INTELLIGENCE 2022年 310卷

作者： Akgun, Ozgur Frisch, Alan M. Gent, Ian P. Jefferson, Christopher Miguel, Ian Nightingale, Peter Univ St Andrews Sch Comp Sci St Andrews KY16 9SX Fife Scotland Univ York Dept Comp Sci Deramore Lane York YO10 5GH N Yorkshire England

When solving a combinatorial problem, the formulation or model of the problem is critical to the efficiency of the solver. Automating the modelling process has long been of interest because of the expertise and time required to produce an effective model of a given problem. We describe a method to automatically produce constraint models from a problem specification written in the abstract constraint specification language ESSENCE. Our approach is to incrementally refine the specification into a concrete model by applying a chosen refinement rule at each step. Any non-trivial specification may be refined in multiple ways, creating a space of models to choose from. The handling of symmetries is a particularly important aspect of automated modelling. Many combinatorial optimisation problems contain symmetry, which can lead to redundant search. If a partial assignment is shown to be invalid, we are wasting time if we ever consider a symmetric equivalent of it. A particularly important class of symmetries are those introduced by the constraint modelling process: modelling symmetries. We show how modelling symmetries may be broken automatically as they enter a model during refinement, obviating the need for an expensive symmetry detection step following model formulation. Our approach is implemented in a system called CONJURE. We compare the models produced by CONJURE to constraint models from the literature that are known to be effective. Our empirical results confirm that CONJURE can reproduce successfully the kernels of the constraint models of 42 benchmark problems found in the literature. (c) 2022 The Authors. Published by Elsevier B.V. This is an open access article under the

关键词： constraint modelling constraint programming Combinatorial optimization constraint satisfaction problem

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Coordinated Route Planning of Multiple Fuel-constrained Unmanned Aerial Systems with Recharging on an Unmanned Ground Vehicle for Mission Coverage

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JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 2022年第1期106卷 30-30页

作者： Ramasamy, Subramanian Reddinger, Jean-Paul F. Dotterweich, James M. Childers, Marshal A. Bhounsule, Pranav A. Univ Illinois Dept Mech & Ind Engn Chicago IL 60607 USA US Army DEVCOM Res Lab Aberdeen Proving Ground MD 21005 USA

Small Unmanned Aerial Systems (sUAS) such as quadcopters are ideal for aerial surveillance because of their runway independence, terrain-agnostic maneuverability, low cost, and simple hardware. However, battery capacity constraints limit the effective range and endurance of sUASs, requiring human intervention to replace batteries or perform manual recharging for longer operations. To increase their range, an Unmanned Ground Vehicle (UGV) may provide recharging depot as needed. The problem is then to find optimal paths for the UGV and sUASs to visit mission points and sUAS-UGV rendezvous points for recharging. We present a three-tiered heuristics to solve this computationally hard combinatorial optimization problem: (1) K-means clustering is used to find UGV waypoints, (2) a traveling salesman formulation (TSP) is used to solve the optimal UGV route, and (3) vehicle routing problem formulation (VRP) with capacity constraints, time windows, and dropped visits is used to solve for sUAS routes. We use constraint programming for optimization of the TSP and VRP, achieving a solution for 25 mission points and up to 4 sUASs in about a minute on a standard desktop computer. We also found that constraint programming solvers are 7 - 30 times faster, but 4 - 15% sub-optimal compared to mixed-integer solvers, which provide exact solutions. Further, we used constraint programming solvers in a Monte-Carlo approach to evaluate the role of mission spread, number of clusters, and number of sUASs on the optimal solution. Our contribution is the development of heuristics for route selection of sUAS-UGVs that produces high quality solutions as more mission points and sUASs are added without substantially increasing the computational time.

关键词： Traveling salesman problem Vehicle routing problem K-means clustering Fuel constraints constraint programming Local search heuristics

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SINPA: SupportINg the automation of construction PlAnning

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EXPERT SYSTEMS WITH APPLICATIONS 2022年第0期190卷 116149-116149页

作者： Canizares, Pablo C. Estevez-Martin, Sonia Nunez, Manuel Autonomous Univ Madrid Modelling & Software Engn Res Grp Comp Sci Dept Madrid Spain Univ Complutense Madrid Design & Testing Reliable Syst Res Grp Madrid 28040 Spain Univ Complutense Madrid Inst Knowledge Technol Madrid 28040 Spain

We present SINPA: an integrated framework to support construction site planners. The most basic functionality of our tool provides a user-friendly framework to represent causality relations (precedence and parallelism) between the different tasks conforming a project. SINPA strongly relies on a constraint solver and makes an intensive use of constraints. SINPA automatically studies optimisations of the original planning, recomputes the solutions and provides recommendations in an intuitive way so that the planners can modify their original plan. It is important to emphasise that the users of SINPA do not need to work with or understand constraint programming.

关键词： constraint programming Construction sites planning Tools to support projects development

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The Sample Analysis Machine Scheduling Problem: Definition and comparison of exact solving approaches

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COMPUTERS & OPERATIONS RESEARCH 2022年 142卷 105730-105730页

作者： Bofill, Miquel Coll, Jordi Martin, Gerard Suy, Josep Villaret, Mateu Univ Girona Girona Spain Aix Marseille Univ Univ Toulon CNRS LIS Marseille France

Nowadays there exists a wide variety of automatic machines that perform analytical tests on liquid samples, such as water, blood, urines, saliva, etc. A test can be modelled as a set of activities with given precedences and through sharing a set of limited resources. A scheduling process is therefore required to find a feasible or optimal execution of a set of tests. An important particularity of the machines performing tests are their storage areas of limited capacity. For instance, one activity may require a sample to be moved to an observation area, while another activity may later remove this sample from that observation area. In this paper, we introduce a real problem encountered in the analytical instrument industry known as the Sample Analysis Machine Scheduling Problem (SAMSP). We show that the SAMSP is a particular case of the Resource Constrained Project Scheduling Problem with Cumulative Resources (RCPSP-Cu), and present a successful application of optimization techniques for it. We are interested in exact approaches, since the models presented will be used to prove the maximum throughput of the selected machine layouts. In particular, we compare the performance of approaches based on constraint programming (CP), Satisfiability Modulo Theories (SMT), and Mixed Integer Linear programming (MILP), on real instances of SAMSP.

关键词： Scheduling RCPSP constraint programming SMT MILP Sample analysis

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