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Optimising the flight turnaround schedules: An improved sliding time windows based on MILP and CP models

COMPUTERS & OPERATIONS RESEARCH 2024年 161卷

作者： Zhang, Sicheng Li, Xiang Yuan, Xing Liu, Jiaming Peng, Jinlin Li, Dongmei China Rongtong Artificial Intelligence Res Ctr Chaoyang 100022 Beijing Peoples R China Changan Univ Sch Econ & Management Xian 710064 Shaanxi Peoples R China Beijing Technol & Business Univ Sch Int Econ & Management Chaoyang 100048 Beijing Peoples R China Natl Inst Def Sci & Technol Innovat Beijing 100071 Peoples R China

This paper addresses the scheduling of turnaround operations for flights in civil airports. A series of complex issues, including the heterogeneity of flights and operators, resource constraints on turnaround operations, temporal restrictions and alternative service patterns of turnaround operations, multi-functional operators, multi-trip services and multi-to-one services, are jointedly considered. We propose two formulations for the problem: A mixed-integer linear programming (MILP) model, and a constraint programming (CP) model. For comparison purpose, we also present simplified versions of the models in which the multi-to-one services are prohibited. The uncertainty are incorporated by modifying the models based on robust optimisation principles. The numerical experiments are conducted using instances generated based on real flight data at Beijing Capital International Airport. It is shown that under current computer configurations, small-scale instances can be solved to the optimum by CPLEX within an acceptable period of time using the MILP model, while moderate-scale instances can be tackled using the CP formulation. To cope with large-scale instances, an improved sliding time window method is developed, and evaluated with different parameter combinations, showing that practical turnaround schedule would best be updated two to three times per hour. Besides, after a case study in both static and stochastic scenarios, we illustrate that multi-to-one services should be specifically considered and highlighted, for their existence could significantly improve the operator utilisation rate and reduce flight delay, especially when the uncertainties are taken into account.

关键词： Flight ground service scheduling Flight turnaround scheduling constraint programming Mixed linear integer programming Airport management

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A global constraint for sequential pattern mining

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Revue d'Intelligence Artificielle 2016年第6期30卷 675-703页

作者： Kemmar, Amina Lebbah, Yahia Loudni, Samir Boizumault, Patrice Charnois, Thierry Université d'Oran 1 Lab. LITIO B.P. 1524 El-M'Naouar Oran31000 Algeria Université de Caen Basse-Normandie GREYC Caen14032 France Université Paris-Nord LIPN Villetaneuse93430 France

Sequential pattern mining under constraints is a challenging data mining task. Many efficient ad hoc methods have been developed for mining sequential patterns, but they are all suffering from a lack of genericity. Recent works have investigated constraint programming (CP) methods, but they are not still effective because of their encoding. In this paper, we propose a global constraint based on the projected databases principle which remedies to this drawback. Experiments show that our approach clearly outperforms CP approaches and competes well with ad hoc methods on large datasets. © 2016 Lavoisier.

关键词： constraint programming

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Multivalued Decision Diagrams for Sequencing Problems

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OPERATIONS RESEARCH 2013年第6期61卷 1411-1428页

作者： Cire, Andre A. van Hoeve, Willem-Jan Carnegie Mellon Univ Tepper Sch Business Pittsburgh PA 15213 USA

Sequencing problems are among the most prominent problems studied in operations research, with primary application in, e.g., scheduling and routing. We propose a novel approach to solving generic sequencing problems using multivalued decision diagrams (MDDs). Because an MDD representation may grow exponentially large, we apply MDDs of limited size as a discrete relaxation to the problem. We show that MDDs can be used to represent a wide range of sequencing problems with various side constraints and objective functions, and we demonstrate how MDDs can be added to existing constraint-based scheduling systems. Our computational results indicate that the additional inference obtained by our MDDs can speed up a state-of-the art solver by several orders of magnitude, for a range of different problem classes.

关键词： sequencing single machine scheduling networks/graphs constraint programming decision diagrams

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Multiskilled Project Management Workforce Assignment across Multiple Projects Regarding Competency

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JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT 2020年第12期146卷

作者： Sarihi, Mohsen Shahhosseini, Vahid Banki, Mohammad Taghi Amirkabir Univ Technol Dept Civil & Environm Engn Construct Engn & Management POB ***424 Hafez Ave Tehran Iran Amirkabir Univ Technol Dept Civil & Environm Engn POB ***424 Hafez Ave Tehran Iran

Contractors attempt to manage optimal collection of human capital that can optimize the company's performance. The skills and competency of human resources contribute considerably to the competitive advantage of the firm. Yet the skill shortage problem encourages utilizing strategies that bring more flexibility to workforce management. Multiskilling has been suggested as a potential strategy that assists workforce assignment across multiple projects. However, it brings new challenges for company workforce managers. This study contributes to the construction project management body of knowledge by proposing a simulation framework for assigning multiskilled, mainly managerial, workforces across multiple projects of one company. Meanwhile, it is a combination of a staffng and scheduling decision model, incorporating workers' competency status. A cohesive mathematical model using the cost objective function optimizes the entire allocation process toward minimizing resource usage and fluctuations, minimizing costs, and maximizing social sustainability. Ultimately, a validation example incorporating diverse workers' competency data is provided to exemplify how the optimization model performs in an academic setting compared with three commonly used methods in workforce assignment. This approach provides insight into simulating workforce assignments across multiple projects regarding competency. (C) 2020 American Society of Civil Engineers.

关键词： Human resources Assignment problem Multiskilling Competency Optimization constraint programming

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A multi-criteria logical based approach for optimal planning and assessment of rule-based hybrid load following micro combined heat and power systems

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ENERGY CONVERSION AND MANAGEMENT 2021年 243卷 114338-114338页

作者： Mohammadi, Hesam Mohammadi, Mohammad Shiraz Univ Sch Elect & Comp Engn Dept Power & Control Engn Shiraz Iran

This study presents a logical based approach with constraint programming technique for applying rule-based hybrid strategies in the optimal planning of the micro cogeneration systems. Moreover, in this paper, a novel operation strategy that relied on the comparison of loss of supply probabilities for reducing the dependency on auxiliary systems and minimizing the production of redundant energy in micro cogeneration systems is also introduced. The presented approach is applied to evaluate the effectiveness of five operation strategies namely two basic, two common hybrid and the proposed hybrid strategy under three single optimization criteria for the total annual cost (TAC), primary energy consumption (PEC) and greenhouse gas generation (GHG) as well as one integrated criterion based on Utopia tracking method for the combination of these criteria. Three energy matching parameters are exploited to assess the performance of each strategy in matching the cogenerated energy carriers with the building demand requirements. The analysis of the obtained results for four types of residential buildings indicates that the common hybrid strategy which maximizes the exploitation of cogeneration system, and the proposed strategy as the most suitable strategies for integrated criterion have been able to achieve the best compromise solutions with over 55%, 14% and 9% reductions in TAC, PEC and GHG respectively. While the proposed strategy can achieve higher reductions for TAC (up to 4.6%) as well as higher overall performance for energy matching (up to 2.5%) with the same limitations bounds for GHG and PEC in comparison to this common hybrid strategy. By analyzing the model uncertainties, the feed-in tariff for power generation with near 60% decrement in TAC is found as the most dominant economic parameter for sensitivity analysis while the capacity of the micro cogeneration unit with over 3% increment is detected as the most affected outcome for stochastic analysis.

关键词： Micro cogeneration Logic-based optimization framework constraint programming Hybrid operation strategy Utopia tracking method Energy matching performance

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A Survey on String constraint Solving

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ACM COMPUTING SURVEYS 2023年第1期55卷 16-16页

作者： Amadini, Roberto Univ Bologna Mura Anteo Zamboni 7 I-40126 Bologna Italy

String constraint solving refers to solving combinatorial problems involving constraints over string variables. String solving approaches have become popular over the past few years given the massive use of strings in different application domains like formal analysis, automated testing, database query processing, and cybersecurity. This article reports a comprehensive survey on string constraint solving by exploring the large number of approaches that have been proposed over the past few decades to solve string constraints.

关键词： String constraint solving constraint programming satisfiability modulo theories automata theory software analysis

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Temporal constrained objects for modelling neuronal dynamics

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PEERJ COMPUTER SCIENCE 2018年第7期4卷 e159页

作者： Nair, Manjusha Kannimoola, Jinesh Manchan Jayaraman, Bharat Nair, Bipin Diwakar, Shyam Amrita Vishwa Vidyapeetham Amrita Sch Biotechnol Kollam Kerala India Amrita Vishwa Vidyapeetham Dept Comp Sci & Applicat Amritapuri Campus Kollam Kerala India Amrita Vishwa Vidyapeetham Ctr Cybersecur Syst & Networks Amritapuri Campus Kollam Kerala India SUNY Buffalo Dept Comp Sci & Engn Buffalo NY USA

Background: Several new programming languages and technologies have emerged in the past few decades in order to ease the task of modelling complex systems. Modelling the dynamics of complex systems requires various levels of abstractions and reductive measures in representing the underlying behaviour. This also often requires making a trade-off between how realistic a model should be in order to address the scientific questions of interest and the computational tractability of the model. Methods: In this paper, we propose a novel programming paradigm, called temporal constrained objects, which facilitates a principled approach to modelling complex dynamical systems. Temporal constrained objects are an extension of constrained objects with a focus on the analysis and prediction of the dynamic behaviour of a system. The structural aspects of a neuronal system are represented using objects, as in object-oriented languages, while the dynamic behaviour of neurons and synapses are modelled using declarative temporal constraints. Computation in this paradigm is a process of constraint satisfaction within a time-based simulation. Results: We identified the feasibility and practicality in automatically mapping different kinds of neuron and synapse models to the constraints of temporal constrained objects. Simple neuronal networks were modelled by composing circuit components, implicitly satisfying the internal constraints of each component and interface constraints of the composition. Simulations show that temporal constrained objects provide significant conciseness in the formulation of these models. The underlying computational engine employed here automatically finds the solutions to the problems stated, reducing the code for modelling and simulation control. All examples reported in this paper have been programmed and successfully tested using the prototype language called TCOB. The code along with the programming environment are available at http://***/compneuro/

关键词： Temporal constrained objects constraint programming Object-oriented languages Declarative modelling Neuron models

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Solving the flexible job shop scheduling and lot streaming problem with setup and transport resource constraints

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2023年第11期54卷 2443-2443页

作者： Yunusoglu, Pinar Yildiz, Seyda Topaloglu Izmir Bakircay Univ Dept Ind Engn Izmir Turkiye Dokuz Eylul Univ Grad Sch Nat & Appl Sci Izmir Turkiye Dokuz Eylul Univ Dept Ind Engn Izmir Turkiye

This article addresses the Flexible Job Shop Scheduling and Lot Streaming Problem (FJSSP-LS) under setup and transport resource constraints. While the related literature emphasises the lot streaming policy for time-based objectives, setup and transport resource constraints were not considered simultaneously with this policy, limiting the resulting schedule's applicability in practice. For this reason, we propose a novel constraint programming (CP) model enriched by an efficient variable and value ordering strategy specifically designed for the FJSSP-LS with resource constraints. We also present a CP-based iterative improvement method, CP-based Large Neighbourhood Search (CP-based LNS), that focuses on exploring large neighbourhoods through the CP model. Both models are initially tested for the FJSSP and have been shown to provide the best solutions to well-known benchmark instances. Next, they are used for the FJSSP-LS, and the proposed CP-based LNS improves the objective function value by 4.68 percent on average compared to the CP model for the generated test problems.

关键词： Flexible job shop scheduling lot streaming resource constraints constraint programming large neighbourhood search

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OPTIMISATION AND constraint BASED HEURISTIC METHODS FOR ADVANCED PLANNING AND SCHEDULING SYSTEMS

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INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE 2016年第1期23卷 26-48页

作者： Ozturk, Cemalettin Ornek, M. Arslan Natl Univ Ireland Univ Coll Cork Insight Ctr Data Analyt Cork Ireland Izmir Univ Econ Dept Ind Engn Izmir Turkey

Manufacturing Resources Planning (MRPII) systems are unable to prevent capacity problems occurring on the shop floor because of the fixed lead time and backward scheduling logic. For this reason, a new breed of concepts called APS (Advanced Planning and Scheduling) systems emerged which include finite capacity planning at the shop floor level through constraint based planning. In this paper, we present a constraint programming (CP) model to show how optimization models could be used in this context. We also present a two phase heuristic to solve this complicated APS problem. While jobs are assigned to the best eligible machines to smooth the workload on the machines in the first phase, a constraint based scheduling heuristic schedules jobs once they are assigned to eligible machines in the second phase. We provide numerical tests and discuss the results for both the model and the heuristic. The concluding remarks and suggestions for future research are stated in the final section of the paper.

关键词： constraint programming advanced planning and scheduling heuristics

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Redefining hybrid flow shop group scheduling: Unveiling a novel hybrid modeling paradigm and assessing 48 MILP and CP models

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SWARM AND EVOLUTIONARY COMPUTATION 2023年 83卷

作者： Wang, Yuting Han, Yuyan Pan, Quan-ke Li, Huan Wang, Yuhang Liaocheng Univ Sch Comp Sci Liaocheng 252059 Peoples R China Shanghai Univ Coll Mech & Elect Engn & Automat Shanghai 200444 Peoples R China

A hybrid flow shop group scheduling problem (HFGSP) involves two distinct sub-problems, the arrangement of groups and the configuration of jobs within each group. Constructing its mathematical model based on the classification of these sub-problems can help better understand the problem's characteristics. However, the existing literature fails to establish MILP models of HFGSP based on the interrelation between each subproblem and the respective process constraints satisfied by each subproblem. To address this gap, our study first categorizes all the constraints in the HFGSP according to several factors: group arrangement, job arrangement within the group, process requirements between groups, process requirements between jobs from the same group, process requirements between adjacent stages, and the relationship between the decision variables of completion time and the objective constraint. Following this classification, we construct 48 available MILP models of HFGSP. Additionally, we also propose an efficient constraint programming (CP) model of HFGSP. Numerous experiments are conducted to verify the correctness and performance of all 48 MILP models across different test instances, analyze the complexities of all models, and excavate their intrinsic characteristics. Through our evaluation for the 48 models, we observe that models 24 and 48 exhibit superior performance. This highlights the effectiveness of the hybrid modeling approach, which synergistically combines sequence-based modeling for groups and position-based adjacent modeling for jobs within each group. The utilization of this hybrid modeling approach enables the construction of high-quality MILP models for addressing the HFGSP problem. Our intention is to bridge the gap between MILP modeling of HFGSP and problem-specific algorithms, thereby providing a comprehensive understanding of the problem and offering potential solutions.

关键词： Hybrid flow shop group scheduling Mixed integer linear programming constraint programming Heuristic algorithm Makespan

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