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Applications of constraint programming in production scheduling problems: A descriptive bibliometric analysis

RESULTS IN CONTROL AND OPTIMIZATION 2024年 14卷

作者： Prata, Bruno A. Abreu, Levi R. Nagano, Marcelo S. Univ Fed Ceara Dept Ind Engn Fortaleza Brazil Univ Sao Paulo Dept Prod Engn Sao Carlos Brazil

Production scheduling is a class of widely studied combinatorial optimization problems. Given the complexity of the most addressed production environments several solution procedures have been proposed. In recent years, operational researcher practitioners have been paying attention to solving production scheduling problems using constraint programming, and growing interest in this research domain has been evidenced. The aim of this study is to report a descriptive bibliometric analysis of applications of constraint programming in production scheduling problems. The scope of the study is limited to reviewing 170 scientific papers published between 1992 and 2023 from the Scopus and Web of Science databases. In our proposed research questions, we could address the main topics studied, the most studied performance measures, and the profile of the analyzed documents. Furthermore, we could identify the main gaps and present suggestions for future research.

关键词： Production scheduling Artificial intelligence constraint programming Methodi ordinatio Bibliometrix

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A constraint programming Approach for the Preference Tourist Trip Design Problem 7th

A Constraint Programming Approach for the Preference Tourist...

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7th International Conference on Optimization and Learning

作者： Riff, Stephanie Castro, Carlos Monfroy, Eric Univ Tecn Feder Santa Maria Valparaiso Chile Univ Nantes Nantes France

ISBN: (纸本)9783031779404;9783031779411

Currently, tourists seek to optimize their time when planning a trip to another country to visit attractions and places that match their tastes and preferences. Among these preferences is slow or relaxed tourism, which demands visiting less popular places and having in mind conscious relaxed tourism. Linear programming has been used in some studies to solve optimization problems related to tourist routes, but its use is limited due to the complexity of the constraints in these problems. In contrast, constraint programming can handle complex constraints more naturally, allowing for better constraint modeling and more efficient problem solving. This paper addresses this problem by using constraint programming techniques for the optimization of tourist routes. constraint programming has been proven to be an effective technique for solving optimization problems related to tourist routes given its ability to model complex constraints and conflicts in solutions naturally. The results obtained in this article demonstrate that constraint programming using complete search techniques provides better results compared to linear programming. In particular, the proposed technique achieved the optimal solution for 70% of the tested instances, surpassing the results obtained by state-of-the-art studies and highlighting its efficiency in execution time. In summary, it is concluded that constraint programming is a more effective and efficient technique than linear programming in optimizing tourist routes in view of its ability to naturally model complex constraints and conflicts in solutions.

关键词： Tourism constraint programming Route planning

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Integrating MiniZinc with ASP Chef: Browser-Based constraint programming for Education and Prototyping 17th

Integrating MiniZinc with ASP Chef: Browser-Based Constraint...

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17th International Conference on Logic programming and Non-monotonic Reasoning

作者： Alviano, Mario Reiners, Luis Angel Rodriguez Univ Calabria DEMACS Via Bucci 30-B I-87036 Arcavacata Di Rende CS Italy

ISBN: (纸本)9783031742088;9783031742095

In this paper, we present the integration of MiniZinc into ASP Chef, expanding its capabilities to include constraint programming alongside Answer Set programming (ASP). By leveraging the web assembly version of MiniZinc, this integration allows for running MiniZinc models directly in the browser, eliminating the need for additional software installations. This browser-based approach is particularly advantageous for educational settings and rapid prototyping, offering a seamless and accessible environment for learners and practitioners. To facilitate the incorporation of MiniZinc in ASP recipes, we have implemented a mapping mechanism that converts facts to MiniZinc data and vice versa. This integration not only broadens the scope of problems that can be addressed using ASP Chef but also simplifies the workflow for users, making it a versatile tool for complex computational tasks.

关键词： Answer Set programming constraint programming system description

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A constraint programming Approach for Aircraft Disassembly Scheduling 1

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21st International Conference on the Integration of constraint programming, Artificial Intelligence, and Operations Research (CPAIOR)

作者： Thomas, Charles Schath, Pierre UCLouvain Ottignies Belgium

ISBN: (数字)9783031605994

ISBN: (纸本)9783031606014;9783031605994

The dismantling and recycling of aircrafts is one of the future challenges for the air transport industry in terms of sustainability. This problem is hard to solve and optimize as planning operations are highly constrained. Indeed, extracting each part requires technicians with the necessary qualifications and equipment. The parts to be extracted are constrained by precedence relations and the number of simultaneous technicians on specific zones is restricted. It is also essential to avoid unbalancing the aircraft during disassembly. Cost is a significant factor, influenced by the duration of ground mobilization and the choice of technicians for each operation. This paper presents a first constraint programming model for this problem using optional interval variables. This model is used to solve variations of a large instance involving up to 1500 tasks, based on real-life data provided by our industrial partner. The results show that the model can find feasible solutions for all variations of the instance and compares the solutions obtained to lower bounds.

关键词： Aircraft Dismantling Scheduling RCPSP constraint programming Application Industrial Problem

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Genetic-based constraint programming for Resource Constrained Job Scheduling

Genetic-based Constraint Programming for Resource Constraine...

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Genetic and Evolutionary Computation Conference (GECCO)

作者： Nguyen, Su Thiruvady, Dhananjay Sun, Yuan Zhang, Mengjie RMIT Univ Sch Accounting Informat Syst & Supply Chain Melbourne Vic Australia Deakin Univ Sch Informat Technol Melbourne Vic Australia La Trobe Univ La Trobe Business Sch Melbourne Vic Australia Victoria Univ Wellington Ctr Data Sci & Artificial Intelligence Wellington New Zealand

ISBN: (纸本)9798400704949

Resource constrained job scheduling is a hard combinatorial optimisation problem that originates in the mining industry. Off-the-shelf solvers cannot solve this problem satisfactorily in reasonable time-frames, while other solution methods such as evolutionary computation methods and matheuristics cannot guarantee optimality and require low-level customisation and specialised heuristics to be effective. This paper addresses this gap by proposing a genetic programming algorithm to discover efficient search strategies of constraint programming for resource-constrained job scheduling. In the proposed algorithm, evolved programs represent variable selectors to be used in the search process of constraint programming, and their fitness is determined by the quality of solutions obtained by constraint programming for training instances. The novelties of this algorithm are (1) a new representation of variable selectors, (2) a new fitness evaluation scheme, and (3) a pre-selection mechanism. Tests with a large set of random and benchmark instances show that the evolved variable selectors can significantly improve the efficiency of constraining programming. Compared to highly customised metaheuristics and hybrid algorithms, evolved variable selectors can help constraint programming identify quality solutions faster and proving optimality is possible if sufficiently large run-times are allowed. The evolved variable selectors are especially helpful when solving instances with large numbers of machines.

关键词： Genetic programming Job scheduling constraint programming

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A block-building constraint programming model for the container loading problem

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COMPUTERS & OPERATIONS RESEARCH 2025年 182卷

作者： Liu, Chang Smith-Miles, Kate Wauters, Tony Costa, Alysson M. Univ Melbourne Sch Math & Stat Melbourne Australia CODeS Leuven Dept Comp Sci Gebroeders Smetstr 1 B-9000 Ghent Belgium Univ Melbourne ARC Training Ctr Optimisat Technol Integrated Meth Melbourne Australia

The container loading problem involves packing a set of given rectangular boxes into a larger rectangular container of fixed size, with the objective of maximizing the volume of the loaded boxes. Most of the literature on the container loading problem and its variants proposes heuristic approaches that can find good solutions quickly. Current exact methods are mostly limited to mixed-integer programming (MIP) formulations, which often struggle to obtain good solutions for large problem instances. In this paper, we introduce two exact constraint programming models for the container loading problem. The first model uses integer and binary variables to assign boxes to valid positions and orientations within the container. The second model enhances this by incorporating the concept of block-building, commonly used in heuristic methods. Extensive computational experiments on classical benchmark instances from the literature show that the solutions obtained with the proposed models significantly outperform those achieved with existing MIP models. We also perform an instance space analysis of the proposed models to map the models' performances across problem instances, providing deeper insights into the strengths and weaknesses of the block-building approach.

关键词： Packing Container loading problem constraint programming Mathematical modeling Block building Instance space analysis

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Solving the Car Sequencing Problem with Cross-Ratio constraints Using constraint programming Approach 11th

Solving the Car Sequencing Problem with Cross-Ratio Constrai...

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11th International Conference on Industrial Engineering and Applications - Europe (ICIEA - Europe)

作者： Jalilvand, Sana Bozorgi-Amiri, Ali Mamoodjanloo, Mehdi Baboli, Armand INSA Lyon LIRIS Lab UMR CNRS 5205 Villeurbanne France Univ Tehran Coll Engn Sch Ind Engn Tehran Iran

ISBN: (纸本)9783031581120;9783031581137

The rise of mass-individualization has underscored the significance of Mixed-Model Assembly Lines (MMALs) for producing diverse products on the same line. The Car Sequencing Problem (CSP) tackles short-term balancing in an MMAL by emphasizing the use of spacing rules to manage the space between each pair of work-intensive products that possess specific characteristics. In this study, we tackle two challenges within the CSP context. The first challenge involves exploring CSP with cross-ratio constraints that takes into account the dependency between different characteristics. As the second challenge, we study the CSP under two states where spacing rule violations are not allowed (hard) and allowed (soft). We develop two constraint programming models for the mentioned states and evaluate the performance of the models using several real-world assembly lines' instances. The findings enhance understanding of each model's strengths and weaknesses. Given the inherent complexity of real-world problems, the soft model may find more practical and effective application. This research enriches the realm of problem-solving in MMALs by offering valuable insights and introducing the main challenges in the CSP.

关键词： Car sequencing problem Mixed-model assembly line constraint programming constraint dependency

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Combining Heuristics and constraint programming for the Parallel Drone Scheduling Vehicle Routing Problem with Collective Drones 15th

Combining Heuristics and Constraint Programming for the Para...

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15th International Conference of the Metaheuristics International Conference (MIC)

作者： Montemanni, Roberto Dell'Amico, Mauro Corsini, Andrea Univ Modena & Reggio Emilia I-42122 Reggio Emilia Italy

ISBN: (纸本)9783031629112;9783031629129

Last-mile delivery problems where trucks and drones collaborate to deliver goods to final customers are considered. We focus on settings where a fleet with several homogeneous trucks work in parallel to collaborative drones, able to combine with each other to optimize speed and power consumption for deliveries. A heuristic for the min-max vehicle routing problem is coupled with constraint programming models, leading to an effective method able to provide several state-of-the-art solutions for the instances commonly adopted in the literature.

关键词： Vehicle Routing constraint programming Heuristics

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Optimization of Reconfigurable Manufacturing Systems Configuration Using constraint programming 43rd

Optimization of Reconfigurable Manufacturing Systems Configu...

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43rd IFIP WG 5.7 International Conference on Advances in Production Management Systems (APMS)

作者： Lovato, Damien Bouzekri, Hamza Sabioni, Rachel Campos Zidi, Slim Capgemini Engn Res & Innovat Dept France 4 Ave Didier Daurat F-31700 Blagnac France PwC France & Maghreb Aerosp & Def Operat 1 Sq Occitane F-31080 Toulouse France

ISBN: (纸本)9783031716393;9783031716379;9783031716362

To cope with market unpredictability and uncertainty, manufacturing industries should be able to rapidly adapt their manufacturing systems to be more responsive to market changes. Reconfigurable Manufacturing Systems (RMS) offer an alternative to traditional manufacturing systems. They can rapidly reconfigure and readapt their capability and functionality to meet new requirements without the need to start from scratch. RMS are complex systems and a critical phase in their implementation involves their design. We propose a new constraint programming approach to minimize the total investment cost of a multi-part flow line configuration. The approach was implemented and tested on a literature case study. The results show the ability of the method to find an optimal solution in few seconds for a small instance.

关键词： Reconfigurable manufacturing systems Multi-part flow line Configuration selection Optimization constraint programming

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constraint programming Approach to Coverage-Path Planning for Autonomous Multi-UAV Infrastructure Inspection

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DRONES 2023年第9期7卷

作者： Matlekovic, Lea Schneider-Kamp, Peter Univ Southern Denmark Dept Math & Comp Sci DK-5230 Odense Denmark

This article presents a constraint modeling approach to global coverage-path planning for linear-infrastructure inspection using multiple autonomous UAVs. The problem is mathematically formulated as a variant of the Min-Max K-Chinese Postman Problem (MM K-CPP) with multi-weight edges. A high-level constraint programming language is used to model the problem, which enables model execution with different third-party solvers. The optimal solutions are obtained in a reasonable time for most of the tested instances and different numbers of vehicles involved in the inspection. For some graphs with multi-weight edges, a time limit is applied, as the problem is NP-hard and the computation time increases exponentially. Despite that, the final total inspection cost proved to be lower when compared with the solution obtained for the unrestricted MM K-CPP with single-weight edges. This model can be applied to plan coverage paths for linear-infrastructure inspection, resulting in a minimal total inspection time for relatively simple graphs that resemble real transmission networks. For more extensive graphs, it is possible to obtain valid solutions in a reasonable time, but optimality cannot be guaranteed. For future improvements, further optimization could be considered, or different models could be developed, possibly involving artificial neural networks.

关键词： multi-UAVs path planning infrastructure inspection constraint programming optimization

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