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Fragmented landscape generator (flsgen): A neutral landscape generator with control of landscape structure and fragmentation indices

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METHODS IN ECOLOGY AND EVOLUTION 2022年第7期13卷 1412-1420页

作者： Justeau-Allaire, Dimitri Blanchard, Gregoire Ibanez, Thomas Lorca, Xavier Vieilledent, Ghislain Birnbaum, Philippe Inst Agron Neo Caledonien IAC Noumea New Caledonia Univ Montpellier INRAE CNRS CIRADIRDAMAP Montpellier France CIRAD UMR AMAP Montpellier France Ctr Genie Ind IMT Mines Albi France

Neutral landscape models have many applications in ecology, such as supporting spatially explicit simulations, developing and evaluating landscape indices. However, current approaches provide few options to produce large landscapes with controlled composition and fragmentation indices. We introduce flsgen (Fragmented Landscape Generator), a new neutral landscape generator that addresses this limitation by providing a high level of control over 14 landscape indices. The main novelty of flsgen is the decomposition of landscape generation into two steps: the solving of a constraint satisfaction problem and the generation of a landscape raster with a stochastic algorithm. The latter relies on a continuous environmental gradient that influences the landscape's spatial configuration. flsgen can generate fine-grained artificial landscapes in small amounts of time, which makes it suited to produce large landscape series systematically. We demonstrate the features of flsgen through three illustrative use cases. flsgen is a practical and efficient tool that expands the current possibilities of neutral landscape models and widens their potential applications. To facilitate its uptake, flsgen is available as free and open-source software through a Java API, a command-line interface or an R package.

关键词： artificial landscape generation constraint programming habitat fragmentation landscape ecology landscape indices neutral landscape

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Diagnostic reasoning with structural analysis and constraint programming for quality improvement of business process management systems

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AI COMMUNICATIONS 2013年第4期26卷 409-411页

作者： Borrego, Diana Univ Seville Seville Spain

Everyday more and more complex and critical processes of organizations' services and operations are automated by using business process management systems. Thereby, there exists a growing interest in improving the quality of these processes (e. g., by avoiding functional faults) to ensure the reachability of business goals and, consequently, for organizations to become more competitive. To this end, four contributions to apply diagnosis techniques for identifying and isolating functional faults at both design-time and run-time are proposed.

关键词： Business process management quality improvement diagnosis constraint programming

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Optimising order picking efficiency in a warehouse and distribution centre: A flexible flow shop scheduling approach 27

Optimising order picking efficiency in a warehouse and distr...

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27th International Conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES 2023

作者： Czerniachowska, Kateryna Lutoslawski, Krzysztof Wroclaw University of Economics and Business Komandorska 118/120 Wroclaw53-345 Poland

The scheduling of order-picking problems is a critical aspect of warehouse and distribution centre operations. The efficient execution of order picking requires determining the sequence in which it is needed to pick items from storage locations, as well as the assignment of employees to different picking tasks. In this paper, we present an approach to optimise the process using the Flexible Flow Shop Scheduling Problem (FFSSP), which encompasses multiple order fulfilment stages performing a set of operations on various machines (groups of employees) assigned to the picking stages (e.g., order creating, product collection, quality control, packing, shipment). The aim of the study was to determine the sequence of operations on the machines to minimise the order completion time while taking into account the available resources. We used IBM'sCP Optimizer. The computational experiments showed, on the one hand, the advantages of solver usage for relatively small instances providing optimal solutions, while on the other hand, it demonstrated its disadvantages as for 11 large instances from 24, optimal solutions were not found. Moreover, in 6 cases from 24 ones, the solution which was found was 94% worse than the optimal one. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： constraint programming distribution centre flexible flow shop scheduling warehouse

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A Novel Mathematical Model for Mixed-Blocking Permutation Flow Shop Scheduling Problem with Batch Delivery 1

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22nd International Symposium for Production Research, ISPR 2022

作者： Kizilay, Damla Çil, Zeynel Abidin Öztop, Hande Bağcı, İclal Department of Industrial Engineering Izmir Democracy University İzmir Turkey

ISBN: (数字)9783031244575

ISBN: (纸本)9783031244568

This study proposes a novel constraint programming model for the mixed-blocking permutation flow shop scheduling problem with batch delivery to minimize the total tardiness and batch cost. A mixture of various blocking type restrictions was considered in the mixed-blocking permutation flowshop part of the studied problem. The mixed-blocking permutation flowshop is integrated with the logistics process via batch delivery decisions. Therefore, the studied problem considers both production and logistics decisions simultaneously. In other words, the logistics decision directly affects the production schedule because customers expect their demands for individual products to be produced and delivered to them in a short time. Information exchange in the logistics and production phases helps companies establish a more flexible production system. The effectiveness of the proposed constraint programming model is verified in an illustrative example. According to the result, the model can be competitive in solving the problem. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： constraint programming

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A constraint programming-based approach to a large-scale energy management problem with varied constraints

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JOURNAL OF SCHEDULING 2013年第6期16卷 629-648页

作者： Brandt, Felix Bauer, Reinhard Voelker, Markus Cardeneo, Andreas Res Ctr Informat Technol D-76131 Karlsruhe Germany Karlsruhe Inst Technol Inst Theoret Informat D-76128 Karlsruhe Germany

This paper addresses a large-scale power plant maintenance scheduling and production planning problem, which has been proposed by the ROADEF/EURO Challenge 2010. We develop two lower bounds for the problem: a greedy heuristic and a flow network for which a minimum cost flow problem has to be solved. Furthermore, we present a solution approach that combines a constraint programming formulation of the problem with several heuristics. The problem is decomposed into an outage scheduling and a production planning phase. The first phase is solved by a constraint program, which additionally ensures the feasibility of the remaining problem. In the second phase we utilize a greedy heuristic-developed from our greedy lower bound-to assign production levels and refueling amounts for a given outage schedule. All proposed strategies are shown to be competitive in an experimental evaluation.

关键词： Maintenance scheduling constraint programming Lower bound Flow network Greedy heuristic

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Parallel drone scheduling vehicle routing problems with collective drones

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COMPUTERS & OPERATIONS RESEARCH 2024年 163卷

作者： Montemanni, Roberto Dell'Amico, Mauro Corsini, Andrea Univ Modena & Reggio Emilia Dept Sci & Methods Engn Via Amendola 2 I-42122 Reggio Emilia Italy

We study last-mile delivery problems where trucks and drones collaborate to deliver goods to final customers. In particular, we focus on problem settings where either a single truck or a fleet with several homogeneous trucks work in parallel to drones, and drones have the capability of collaborating for delivering missions. This cooperative behavior of the drones, which are able to connect to each other and work together for some delivery tasks, enhance their potential, since connected drone has increased lifting capabilities and can fly at higher speed, overcoming the main limitations of the setting where the drones can only work independently. In this work, we contribute a constraint programming model and a valid inequality for the version of the problem with one truck, namely the Parallel Drone Scheduling Traveling Salesman Problem with Collective Drones and we introduce for the first time the variant with multiple trucks, called the Parallel Drone Scheduling Vehicle Routing Problem with Collective Drones. For the latter version of the problem, we propose two constraint programming models and a Mixed Integer Linear programming model. An extensive experimental campaign leads to state-of-the-art results for the problem with one truck and some understanding of the presented models' behavior on the version with multiple trucks. Some insights about future research are finally discussed.

关键词： Parallel Drone Scheduling Vehicle Routing Problems with cooperative drones constraint programming Mixed Integer Linear programming Parallel Drone Scheduling Traveling Salesman

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Solving the Extended Job Shop Scheduling Problem with AGVs - Classical and Quantum Approaches 1

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19th International Conference on the Integration of constraint programming, Artificial Intelligence, and Operations Research (CPAIOR)

作者： Geitz, Marc Grozea, Cristian Steigerwald, Wolfgang Stoehr, Robin Wolf, Armin Telekom Innovat Labs Berlin Germany Fraunhofer FOKUS Berlin Germany

ISBN: (数字)9783031080111

ISBN: (纸本)9783031080111;9783031080104

In this article we approach an extended Job Shop Scheduling Problem (JSSP). The goal is to create an optimized duty roster for a set of workpieces to be processed in a flexibly organized workshop, where the workpieces are transported by one or more Autonomous Ground Vehicles (AGV), that are included in the planning. We are approaching this extended, more complex variant of JSSP (still NP-complete) using constraint programming (CP) and Quantum Annealing (QA) as competing methods. We present and discuss: a) the results of our classical solution based on CP modeling and b) the results with modeling as quadratic unconstrained binary optimisation (QUBO) solved with hybrid quantum annealers from D-Wave, as well as with tabu search on current CPUs. The insight we get from these experiments is that solving QUBO models might lead to solutions where some immediate improvement is achievable through straight-forward, polynomial time postprocessing. Further more, QUBO proves to be suitable as an approachable modelling alternative to the expert CP modelling, as it was possible to obtain for medium sized problems similar results, but requiring more computing power. While we show that our CP approach scales now better with increased problem size than the hybrid Quantum Annealing, the number of qubits available for direct QA is increasing as well and might eventually change the winning method.

关键词： constraint programming Job Shop Scheduling Quadratic Unconstrained Boolean Optimization Problem Quantum Annealing Quantum Computing Sequence-Dependent Setup-Times

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Fast scheduling of human-robot teams collaboration on synchronised production-logistics tasks in aircraft assembly

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ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING 2024年 85卷

作者： Guo, Daqiang Univ Cambridge Inst Mfg IfM Ctr Int Mfg Dept Engn 17 Charles Babbage Rd Cambridge CB3 0FS England

The deployment of human-robot teams (HRTs) promises to realise the potential of each team member regarding their distinct abilities and combines efficiency and flexibility in manufacturing operations. However, enabling effective coordination amongst collaborative tasks performed by humans and robots while ensuring safety and satisfying specific constraints is challenging. Motivated by real-world applications that Boeing and Airbus adopt HRTs in manufacturing operations, this paper investigates the allocating and coordinating of HRTs to support safe and efficient human-robot collaboration on synchronised production-logistics tasks in aircraft assembly. We connect the operations research and robotics communities by formulating the problem with precedence constraints, spatial constraints, temporal constraints, and synchronisation constraints that fits within the classic multi-robot task allocation (MRTA) category into a flexible job shop scheduling problem. Two exact approaches, including mixed-integer linear programming (MILP) and constraint programming (CP), are proposed to formulate and solve this problem. A benchmark set with 80 instances (e.g., small/medium-scale and large-scale instances) that corresponds to real dimensions of industrial problems with production tasks, subtasks, locations, deadlines, human worker eligibility and capacity, robot eligibility and capacity, material handling system capacity, and travel times is developed. Experimental evaluation with a total of 1200 independent tests on the benchmark set shows the superiority of the CP approach comparing the MILP approach for efficiently solving real-life scheduling problems of HRTs collaboration on synchronised production-logistics tasks in aircraft assembly.

关键词： Human -robot teams collaboration Synchronised production -logistics Multi -robot task allocation Flexible job shop scheduling constraint programming Mixed -integer linear programming

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Abstract Argumentation for Explainable Satellite Scheduling 9

Abstract Argumentation for Explainable Satellite Scheduling

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9th IEEE International Conference on Data Science and Advanced Analytics (DSAA)

作者： Powell, Cheyenne Riccardi, Annalisa Univ Strathclyde Mech & Aerosp Engn Glasgow Lanark Scotland

ISBN: (纸本)9781665473309

Satellite schedules are derived from satellite mission objectives, which are mostly managed manually from the ground. This increases the need to develop autonomous on-board scheduling capabilities and reduce the requirement for manual management of satellite schedules. Additionally, this allows the unlocking of more capabilities on-board for decision-making, leading to an optimal campaign. However, there remain trust issues in decisions made by Artificial Intelligence (AI) systems, especially in risk-averse environments, such as satellite operations. Thus, an explanation layer is required to assist operators in understanding decisions made, or planned, autonomously on-board. To this aim, a satellite scheduling problem is formulated, utilizing real world data, where the total number of actions are maximised based on the environmental constraints that limit observation and down-link capabilities. The formulated optimisation problem is solved with a constraint programming (CP) method. Later, the mathematical derivation for an Abstract Argumentation Framework (AAF) for the test case is provided. This is proposed as the solution to provide an explanation layer to the autonomous decision-making system. The effectiveness of the defined AAF layer is proven on the daily schedule of an Earth Observation (EO) mission, monitoring land surfaces, demonstrating greater capabilities and flexibility, for a human operator to inspect the machine provided solution.

关键词： Satellite Scheduling Earth Observation constraint programming Abstract Argumentation Optimization Feasibility Explainability Explainable Artificial Intelligence Decision-making Framework

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A multistage optimisation algorithm for the large vehicle routing problem with time windows and synchronised visits

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2021年第11期72卷 2396-2411页

作者： Polnik, Mateusz Riccardi, Annalisa Akartunali, Kerem Univ Strathclyde Mech & Aerosp Engn Glasgow Lanark Scotland Univ Strathclyde Management Sci Glasgow Lanark Scotland

We propose a multistage algorithm for the vehicle routing problem with time windows and synchronised visits, which is capable of solving large problem instances arising in home health care applications. The algorithm is based on a constraint programming formulation of the daily home care scheduling and routing problem. It contains visits with hard time windows and pairwise synchronisation to be staffed by carers who have different skills and work custom shift patterns with contractual breaks. In a computational study, we first experiment with a benchmark set from the literature for the vehicle routing problem with time windows and synchronised visits. Our algorithm reproduced the majority of the best-known solutions, and strictly improved results for several other instances. Most importantly, we demonstrate that the algorithm can effectively solve real scheduling instances obtained from a UK home care provider. Their size significantly surpass similar scheduling problems considered in the literature. The multistage algorithm solved each of these instances in a matter of minutes, and outperformed human planners, scheduling more visits and significantly reducing total travel time.

关键词： Vehicle routing scheduling constraint programming health services practice of OR

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