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A hybrid constraint programming and cross-entropy approach for balancing U-Shaped disassembly line with flexible workstations and spatial constraints

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JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION 2025年 45卷

作者： Zhang, Yu Zhang, Zeqiang Chu, Feng Mammar, Said Southwest Jiaotong Univ Sch Mech Engn Technol & Equipment Rail Transit Operat & Maintena Chengdu 610031 Peoples R China Southwest Jiaotong Univ Tangshan Inst Tangshan 063000 Peoples R China Univ Paris Saclay Univ Evry Blvd Francois Mitterrand F-91000 Evry France

Disassembly lines are an effective means for the large-scale, industrialized recycling of end-of-life products. Among these, U-shaped disassembly lines are particularly noted for their combination of flexibility and production efficiency. This study addresses the U-shaped disassembly line balancing problem, considering the coexistence of separate stations and spatial limitations within workstations. A mixed-integer nonlinear programming model and a constraint programming model are developed to accurately capture this complex problem. Additionally, a novel hybrid constraint programming with a goal-driven cross-entropy optimization algorithm (CP-GDCE) is introduced. This algorithm combines a multi-objective cross-entropy grouping framework, a constraint programming-based heuristic initialization, a multi-point crossover recombination mechanism, and large neighborhood search techniques, significantly enhancing solution efficiency and accuracy. Extensive benchmarking and experimental validation indicate that the CP-GDCE not only excels in addressing the specific problem of this study but also demonstrates superiority in classic disassembly line balancing issues. In 21 test cases, the CP-GDCE achieved superior hypervolume and inverted generational distance values compared to 11 benchmark algorithms. A practical application using a printer disassembly example shows that the proposed U-shaped configuration is highly flexible and efficient, compatible with both traditional U-shaped and straight disassembly lines. This configuration significantly reduces the total length of the disassembly line, improving space utilization and highlighting its practical potential and advantages.

关键词： U-shaped disassembly line Flexible workstation Spatial limitation Mixed-integer programming constraint programming Cross-entropy method

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A multi-stage constraint programming approach to solve clustering problems in open-pit mine planning

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ENGINEERING OPTIMIZATION 2025年第4期57卷 1111-1134页

作者： Mariz, Jorge Luiz Valenca Peroni, Rodrigo de Lemos Silva, Ricardo Martins de Abreu Badiozamani, Mohammad Mahdi Askari-Nasab, Hooman Univ Fed Rio Grande do Sul Min Engn Dept Porto Alegre Brazil Univ Fed Pernambuco Comp Ctr Recife Brazil Univ Alberta Sch Min & Petr Engn Edmonton AB Canada

The open-pit mine sequencing considering blocks with precedence is an NP-hard problem, which can be subdivided into long-, medium- and short-term plans, and requires different information and constraints in each stage. Through the aggregation of blocks into mining cuts, the size of the mine sequencing problem can be reduced and operational constraints can be added. In this study, a multi-stage constraint programming approach to tackle the mining cut clustering problem through a mixed integer linear programming model is proposed, as well as a geometric propagation heuristic to refine the solution. Unlike previously published studies, this approach optimizes the assignment of blocks to clusters and corrects their boundaries considering the size of the mining equipment. The methodology was validated on a real gold-ore data set. Feasible solutions were obtained in an acceptable computation time, while solutions which allowed more clusters increased their objective function and profit by up to 60%.

关键词： Short-term mine planning mining cut clustering constraint programming geometric propagation heuristic

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The dual-resource-constrained re-entrant flexible flow shop a constraint programming approach and a hybrid genetic algorithm

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2025年第5期63卷 1803-1824页

作者： Mlekusch, Johanna Hartl, Richard F. Univ Vienna Dept Business Decis & Analyt A-1010 Vienna Austria

The dual-resource-constrained re-entrant flexible flow shop scheduling problem represents a specialised variant of the flow shop scheduling problem, inspired by real-world scenarios in screen printing industries. Besides the well-known flow shop structure, stages consist of identical parallel machines and operations may re-enter the same stage multiple times before completion. Moreover, each machine must be operated by a skilled worker, making it a dual-resource-constrained problem according to the existing literature. The objective is to minimise the total length of the production schedule. To address this problem, our study employs two methods: a constraint programming model and a hybrid genetic algorithm with a single-level solution representation and an efficient decoding heuristic. To evaluate the performance of our methods, we conducted a computational study using different problem instances. Our findings demonstrate that the proposed hybrid genetic algorithm consistently delivers high-quality solutions, particularly for large instances, while also maintaining a short computational time. Additionally, our methods improve existing benchmark results for instances from the literature for a subclass of the problem. Furthermore, we provide managerial insights into how dual-resource constraints affect the solution quality and the efficiency associated with different workforce configurations in the described production setting.

关键词： Production flexible re-entrant flow shop scheduling dual-resource hybrid genetic algorithm constraint programming

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A constraint programming-based lower bounding procedure for the job shop scheduling problem

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COMPUTERS & OPERATIONS RESEARCH 2025年 177卷

作者： Yuraszeck, Francisco Mejia, Gonzalo Rossit, Daniel Alejandro Luer-Villagra, Armin Univ Andres Bello Dept Engn Sci Quillota 980 Vina Del Mar 2531015 Chile Univ La Sabana Fac Engn Campus Puente Comun Km 7 Autopista Norte Bogota Chia 250001 Colombia Univ Nacl UNS Dept Engn Bahia Blanca Argentina Univ Nacl Sur UNS CONICET INMABB Bahia Blanca Argentina Univ Andres Bello Dept Engn Sci Autopista Concepc Talcahuano 7100 Talcahuano Chile

This paper presents a novel constraint programming (CP) approach to obtain strong lower bounds for the Job Shop Scheduling Problem (JSSP) under the makespan criterion. Our approach comprises two phases. In the first phase, a relaxation of the original problem is solved, while in the second phase, this relaxation is iteratively tightened until a time limit is reached or no better bounds are found. We tested our procedure with 80 JSSP open instances, and the results validated our approach as we were able to find 7 new lower bounds and prove optimality in one instance.

关键词： Scheduling Job shop Lower bound Resource-constrained project scheduling problem constraint programming

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Combining constraint programming and a participatory approach to design agroecological cropping systems

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AGRICULTURAL SYSTEMS 2025年 222卷

作者： Challand, Margot Vismara, Philippe de Tourdonnet, Stephane Univ Montpellier Inst Agro Montpellier ABSys CIHEMCIRADINRAE Montpellier France Univ Montpellier Inst Agro Montpellier MISTEA INRAE Montpellier France Univ Montpellier LIRMM CNRS 161 Rue Ada Montpellier France

Context: Agroecology implementation around the world have shown that increasing the complexity of the agroecosystem leads to increased resilience, lower dependence on synthetic inputs, the provision of ecosystem services and improved performance. However, designing diversified agroecosystems is particularly complex because of the diverse factors to take into account for each specific local context and the range of possible spatiotemporal crop combinations. Objective: Here we propose an iterative agroecological design approach combining artificial intelligence with constraint programming and co-design workshops with farmers to explore and optimize spatiotemporal cropping arrangements in diversified cropping systems. Methods: Our iterative approach comprises a three-step loop for designing new cropping systems: 1) identifying problem data and spatiotemporal constraints;2) applying a flexible constraint programming model, and refining/removing constraints iteratively with farmers' input until a solution is found;and 3) evaluating solutions through model assessment and workshops with farmers, leading to the design of a new scenario if necessary (repeating step 2). We applied our approach to a case study involving diversified mixed fruit tree-vegetable cropping systems in southern France, whereby farmers were involved in co-design workshops with an agronomist. Results and conclusions: The constraint programming model simulated most important farmers' constraints while adapting to the input of new information during the design process. The workshops facilitated knowledge elicitation, with progressive questioning of farming practices, while fostering a learning process through farmer- agronomist discussions. Meanwhile, the scope of the problem was iteratively outlined during the process, driven by the need to seek trade-offs between all of the constraints, and informed by model feedback. This approach allowed farmers to explore and assess disruptive scenarios, in turn faci

关键词： Agroecological design Spatiotemporal arrangement constraint programming Participatory approach Mixed horticultural systems

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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 Flexible Scheduling Framework for Repetitive Construction Projects Based on constraint programming

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Journal of Construction Engineering and Management 2025年第7期151卷

作者： Cao, Qiangnan Zou, Xin Zhang, Lihui School of Economics and Management North China Electric Power Univ. Beijing102206 China Dept. of Economic Management North China Electric Power Univ. Hebei071003 China

Scheduling repetitive construction projects (RCPs) is a challenging task due to the nature of the activities involved. It requires careful consideration of both flexibility and computational performance. This paper develops a versatile RCP scheduling framework applicable to multiple construction scenarios, providing greater flexibility than existing models. The framework incorporates various scheduling features for repetitive activities, such as soft logic, multiskilled crews, multimode execution, crew transfers, and continuous or noncontinuous execution. It also offers optional optimization objectives, such as minimizing the overall project duration, total cost, crew interruption time, and number of employed crews. Planners can combine the features of repetitive activities and choose one or more objectives to meet their needs and preferences. The proposed framework is based on constraint programming, which balances computational efficiency and solution quality while remaining user-friendly. The practicality and effectiveness of the framework are verified through three case studies involving five real-life projects. The results demonstrate that the proposed framework can produce RCP schedules with shorter duration, lower costs, or reduced resource utilization compared with those generated by existing models. © 2025 American Society of Civil Engineers.

关键词： constraint programming

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A constraint programming Model For Serial Batch Scheduling With Minimum Batch Size

arXiv

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arXiv 2025年

作者： Huertas, Jorge A. Van Hentenryck, Pascal Georgia Institute of Technology AtlantaGA United States

In serial batch (s-batch) scheduling, jobs are grouped in batches and processed sequentially within their batch. This paper considers multiple parallel machines, nonidentical job weights and release times, and sequence-dependent setup times between batches of different families. Although s-batch has been widely studied in the literature, very few papers have taken into account a minimum batch size, typical in practical settings such as semiconductor manufacturing and the metal industry. The problem with this minimum batch size requirement has been mostly tackled with dynamic programming and meta-heuristics, and no article has ever used constraint programming (CP) to do so. This paper fills this gap by proposing, for the first time, a CP model for s-batching with minimum batch size. The computational experiments on standard cases compare the CP model with two existing mixed-integer programming (MIP) models from the literature. The results demonstrate the versatility of the proposed CP model to handle multiple variations of s-batching;and its ability to produce, in large instances, better solutions than the MIP models faster. Copyright © 2025, The Authors. All rights reserved.

关键词： constraint programming

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An adapted constraint-programming formulation of the resource-constrained project scheduling problem applied to the identical parallel machines group shop and mixed shop scheduling problems

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2025年第3期32卷 1422-1441页

作者： Yuraszeck, Francisco Mejia, Gonzalo Luer-Villagra, Armin Univ Andres Bello Dept Engn Sci Quillota 980 Vina Del Mar 2531015 Chile Univ La Sabana Campus Puente Comun Km 7 Autopista Norte Bogota Chia 250001 Colombia Univ Andres Bello Dept Engn Sci Autopista Concepc Talcahuano 7100 Vina Del Mar Chile

In this paper, we study the group shop and the mixed shop scheduling problems with single and identical parallel machines at each workstation with the makespan criterion. We adapted a constraint programming formulation previously presented for the classical resource-constrained project scheduling problem. The effectiveness of our approach is evident in the fact that it achieved optimality in 107 out of 130 classical group shop scheduling problem instances and in 320 classical mixed shop scheduling problem instances. In the last set, we obtained 13 new optimal solutions.

关键词： resource-constrained project scheduling group shop stage shop mixed shop parallel machines constraint programming job shop open shop

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