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Optimization of the integrated problem of employee timetabling and job shop scheduling

COMPUTERS & OPERATIONS RESEARCH 2022年 137卷 105332-105332页

作者： Frihat, Mohamed B.Hadj-Alouane, Atidel Sadfi, Cherif Univ Tunis El Manar Natl Engn Sch Tunis OASIS Lab Tunis Tunisia

This paper deals with a real manufacturing scheduling problem that is particularly encountered in the tannery industries. This problem often integrates employee timetabling and production scheduling. The employee timetabling problem is addressed in the context of skill requirements and under availability and legislative constraints. The production scheduling is considered as a re-entrant hybrid job-shop problem with time lags and sequence dependent setup times, under machine availability constraints. The objective is to minimize the labor cost, while respecting a maximum makespan and a maximum tardiness constraints. Two different models and exact resolution methods are proposed, using mixed integer Linear programming (MILP) and Constraint programming (CP). Numerical experimentations are conducted to compare and evaluate their performances, based on randomly generated instances. The results show that the CP model is slower than the MILP model in terms of finding optimal solutions for large instances, but is more efficient in generating feasible solutions. Thus, providing a feasible initial solution to the MILP model using the CP model is a promising hybrid approach to reduce the computational time.

关键词： Employee timetabling Job-shop mixed integer programming Constraint programming

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Simultaneously exploiting two formulations: An exact benders decomposition approach

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COMPUTERS & OPERATIONS RESEARCH 2020年 123卷 105041-105041页

作者： Lusby, Richard Martin Gamst, Mette Ropke, Stefan Spoorendonk, Simon Tech Univ Denmark Dept Technol Management & Econ Lyngby Denmark Energinetdk Tonne Kjaersvej 65 DK-7000 Fredericia Denmark Flowty ApS Copenhagen Denmark

When modelling a given problem using integer linear programming techniques several possibilities often exist, each resulting in a different mathematical formulation of the problem. Usually, advantages and disadvantages can be identified in any single formulation. In this paper we consider mixed integer linear programs and propose an approach based on Benders decomposition to exploit the advantages of two different formulations when solving a problem. We propose applying Benders decomposition to a combined formulation, comprised of two separate formulations, augmented with linking constraints to ensure consistency between the decision variables of the respective formulations. We demonstrate the applicability of the proposed methodology to situations in which one of the formulations models a relaxation of the problem and to cases where one formulation is the Dantzig-Wolfe reformulation of the other. The proposed methodology guarantees a lower bound that is as good as the tighter of the two formulations, and we show how branching can be performed on the decision variables of either formulation. Finally, we test and compare the performance of the proposed approach on publicly available instances of the Cutting Stock Problem and the Split Delivery Vehicle Routing Problem. Compared to the best approaches from the literature, the proposed method shows promising performance and appears to be an attractive alternative. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： mixed integer programming Benders decomposition Cutting stock problem Split delivery vehicle routing

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Security constrained DC OPF considering generator responses

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ELECTRIC POWER SYSTEMS RESEARCH 2021年 192卷 106920-106920页

作者： Ma, Minyue Fan, Lingling Univ S Florida Dept Elect Engn Tampa FL 33620 USA

Considering generator responses after contingencies provides a more practical solution to security constrained direct current optimal power flow (DCOPF) problems. The major difficulty of solving such OPF includes the large number of contingencies and non-convexity of the generator response constraints. In the literature, mixed-integer linear programming (MILP) formulation relying on big-M technique has been applied to deal with the non convexity of generator response constraints. In this paper, we further improve the solving speed by formulating generator response constraints via bilinear expressions and adopting Benders' decomposition technique to decompose the problem into a master problem and multiple subproblems, with each subproblem associated with a contingency. Benders' decomposition strategies were investigated in this research to seek an efficient decomposition approach. Through preserving bilinear expressions related to the base case power while relaxing the rest bilinear expressions via McCormick envelops, we designed an efficient Benders' decomposition strategy. Case study results demonstrate the efficiency of the proposed formulation compared to the state-of-the-art formulations.

关键词： Security constrained optimal power flow Generator response Benders' Decomposition Bilinear formulation mixed integer programming

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Optimal policies for managing aggregate resources on temporary forest roads

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WESTERN JOURNAL OF APPLIED FORESTRY 2006年第4期21卷 207-216页

作者： Sessions, John Boston, Kevin Thoreson, Rick Mills, Keith Oregon State Univ Dept Forest engn Corvallis OR 97331 USA Oregon Dept Forestry Astoria Dist Astoria OR 97103 USA Oregon Dept Forestry Salem OR 97310 USA

High-quality, durable rock aggregate suitable for road surfacing, with low sediment-producing characteristics, is a scarce resource in many forested areas of the United States and elsewhere. Rock aggregate is a heavy product that generally must be transported less than 50 miles to be economically useful. In the Coast Ranges of western Oregon and Washington, aggregate for road surfacing can amount to more than 60% of the cost of road construction. Durable aggregate is becoming scarcer, with few known quarry sources. So, over the last two decades, some aggregate surfacing on temporary roads has been recycled by both the USDA Forest Service and the Oregon Department of Forestry. We discuss the process of recycling road aggregate, drawing from the experience on the Astoria District of the Oregon Department of Forestry, and then propose a mathematical formulation to determine optimal policies for managing aggregate resources on temporary forest roads.

关键词： low-volume road surfacing forest transportation planning aggregate recycling mixed integer programming

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Comparing contingency fire containment strategies using simulated random scenarios

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NATURAL RESOURCE MODELING 2021年第1期34卷 e12295-e12295页

作者： Wei, Yu Thompson, Matthew P. Belval, Erin Gannon, Benjamin Calkin, David E. O'Connor, Christopher D. Colorado State Univ Dept Forest & Rangeland Stewardship Ft Collins CO 80523 USA USDA US Forest Serv Rocky Mt Res Stn Human Dimens Program Ft Collins CO USA USDA US Forest Serv Rocky Mt Res Stn Human Dimens Program Missoula MT USA

Contingency firelines can be used to back up primary lines to increase probability of fire containment, decrease fire losses, and improve firefighter safety. In this study, we classify firelines into primary, contingency, and response lines. We design a modeling process to iteratively implement a mixed integer programming model to evaluate contingency strategies under randomly generated fireline breaching scenarios. Our objectives include: (1) gaining conceptual understanding of the effectiveness of using contingency containers in a fireline network, and (2) suggesting future data collection and model improvement directions to support contingency strategy planning. We evaluate the effectiveness of several model generated containment strategies: only responding to observed primary line breaches, being proactive by implementing a system-level contingency plan, or constructing contingency lines to back up a proportion of a primary container. Data from the Ferguson Fire in California are used to derive a set of hypothetical test cases with different fireline breaching risks to support sensitivity analysis. For comparison, we also test a contingency plan inspired by the Ferguson Fire operation. Analyses suggest that a contingency plan will provide the greatest benefit when fireline breaching risk is high. This study also suggests there are significant data and knowledge gaps that must be addressed to make the model suitable for operational use. Recommendations for Resource Managers Systems analysis can help evaluate contingency containment plans. A contingency plan will provide the greatest benefit when fireline breaching risk is high. It is often efficient to strategically locate contingency lines to back up primary lines with high breaching probabilities. A good contingency plan may help lower fire loss and save suppression effort under many fireline breaching scenarios. Data collection and synchronization are important in supporting future advances in fire containment

关键词： fireline contingency mixed integer programming risk management wildland fire suppression

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Optimizing facility maintenance planning under uncertainty

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JOURNAL OF BUILDING ENGINEERING 2023年 77卷

作者： Betz, Trevor El-Rayes, Khaled Grussing, Michael Bartels, Louis US Army Corps Engineers Engineer Res & Dev Ctr 2902 Newmark Dr Champaign IL 61822 USA Univ Illinois Dept Civil & Environm Engn Urbana IL 61801 USA

Maintenance of civil infrastructure is necessary to ensure assets perform as intended over their service life. As these elements age and degrade, appropriate repair planning helps ensure continued operation. Unfortunately, optimal repair planning can be complex due to uncertainty regarding component conditions. This uncertainty also makes budgeting difficult. This paper presents a novel methodology for optimizing maintenance planning of facility components under uncertainty. The proposed methodology integrates a Markov chain Monte Carlo process to capture the uncertainty inherent in equipment degradation, and a mixed integer programming model to generate an optimal repair plan and an associated minimized budget. This approach identifies an optimal set of facility components that need to be repaired to minimize the total facility repair cost required to meet or exceed a user-defined goal for facility health. The proposed method has distinct advantages over many non-linear approaches in literature as it can guarantee an optimal solution with significantly lower computational time. This computational advantage enables the technique to scale to more significant problems, such as determining repair plans across a portfolio of facilities. The method outperforms basic decision heuristics used to define repair plans and existing non-linear optimization methods in terms of consistently meeting a facility health metric at a minimal cost. Data obtained from the U.S. Army Corps of Engineers is used within a case study to demonstrate the feasibility of the proposed approach as it applies to building infrastructure maintenance.

关键词： mixed integer programming Repair planning Budget estimation

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Solving the green reverse logistics problem in e-commerce using a reinforcement learning based genetic algorithm

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ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS 2024年 68卷

作者： Li, Min-Yang Shih, Fang-Yu Natl Cheng Kung Univ Dept Ind & Informat Management 1 Univ Rd Tainan 70101 Taiwan

This study explores the two-phase green reverse logistics problem with time windows and a focus on perishable items that pose a significant challenge in the management of returned goods in e-commerce. We proposed a mixed integer programming model that considers carbon emissions, fuel consumption costs, facility establishment and operating costs, among other factors. We incorporated reinforcement learning concepts to adjust parameters in traditional genetic algorithms, which often have inflexible parameter settings, thereby enhancing both the efficiency and quality of the solutions. The Q-learning algorithm was adopted as the learning method, and various action combinations of reinforcement learning were explored and compared. We further evaluated the performance of different genetic algorithm variations. The results indicate that the proposed algorithm provides high-quality solutions, and that effective parameter configuration significantly impacts the algorithm's overall performance.

关键词： Reinforcement learning mixed integer programming Green logistics Reverse logistics Alternative fuel vehicles

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Air traffic flow management with layered workload constraints

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COMPUTERS & OPERATIONS RESEARCH 2021年 127卷 105159-105159页

作者： Mannino, Carlo Nakkerud, Andreas Sartor, Giorgio Dept Math POB 1053 Blindern N-0316 Oslo Norway SINTEF POB 124 Blindern N-0314 Oslo Norway

Many regions of the world are currently struggling with congested airspace, and Europe is no exception. Motivated by our collaboration with relevant European authorities and companies in the Single European Sky ATM Research (SESAR) initiative, we investigate novel mathematical models and algorithms for supporting the Air Traffic Flow Management in Europe. In particular, we consider the problem of optimally choosing new (delayed) departure times for a set of scheduled flights to prevent en-route congestion and high workload for air traffic controllers while minimizing the total delay. This congestion is a function of the number of flights in a certain sector of the airspace, which in turn determines the workload of the air traffic controller(s) assigned to that sector. We present a MIP model that accurately captures the current definition of workload, and extend it to overcome some of the drawbacks of the current definition. The resulting scheduling problem makes use of a novel formulation, Path&Cycle, which is alternative to the classic big-M or time-indexed formulations. We describe a solution algorithm based on delayed variable and constraint generation to substantially speed up the computation. We conclude by showing the great potential of this approach on randomly generated, realistic instances. (C) 2020 The Author(s). Published by Elsevier Ltd.

关键词： Hotspot problem Air traffic management Air traffic flow management Scheduling Job-shop scheduling Optimization mixed integer programming Linear programming

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Green logistics oriented tug scheduling for inland waterway logistics

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ADVANCED ENGINEERING INFORMATICS 2021年 49卷 101323-101323页

作者： Zhu, Shengyan Gao, Jiajing He, Xueting Zhang, Shuanglu Jin, Ying Tan, Zheyi Yibin Univ Sanjiang Res Inst Artificial Intelligence & Robot Chengdu Sichuan Peoples R China Shanghai Univ Sch Management Shang Da Rd 99 Shanghai 200444 Peoples R China

Under the global consensus on reducing emissions, shipping companies are undertaking the social responsibility of greenhouse gas emission reduction. Meanwhile, it is a top priority for shipping companies to arrange the tugs and barges reasonably and achieve the goal of energy saving as well as emission reduction. Based on the above problem, this paper proposes a mixed integer programming (MIP) model to jointly optimize the transport routes of tugs considering the barge transshipment, with the objective of minimizing the sum of the carbon emissions for barges handling, tugs travelling and waiting. In the view of specific problem, a Variable Neighborhood Search (VNS) algorithm is designed to solve this MIP model effectively. Numerical experiments based on different sizes of instances are implemented to validate the effectiveness of the proposed algorithm. Computational results indicate that the proposed model reduces carbon emissions by about 46.93% compared to the dispatching rule. Moreover, the consideration of barge transshipment in the model can reduce carbon emissions by about 10.46%. In addition, the VNS algorithm yields solutions with optimality gaps about 0.29% in a short time.

关键词： Inland waterway logistics Sustainable logistics Transshipment of barges mixed integer programming Variable Neighborhood Search algorithm

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A robust SVM-based approach with feature selection and outliers detection for classification problems

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EXPERT SYSTEMS WITH APPLICATIONS 2021年 178卷 115017-115017页

作者： Baldomero-Naranjo, Marta Martinez-Merino, Luisa I. Rodriguez-Chia, Antonio M. Univ Cadiz Fac Ciencias Dept Estadist & Invest Operat Cadiz Spain Univ Sevilla IMUS Inst Matemat Seville Spain

This paper proposes a robust classification model, based on support vector machine (SVM), which simultaneously deals with outliers detection and feature selection. The classifier is built considering the ramp loss margin error and it includes a budget constraint to limit the number of selected features. The search of this classifier is modeled using a mixed-integer formulation with big M parameters. Two different approaches (exact and heuristic) are proposed to solve the model. The heuristic approach is validated by comparing the quality of the solutions provided by this approach with the exact approach. In addition, the classifiers obtained with the heuristic method are tested and compared with existing SVM-based models to demonstrate their efficiency.

关键词： Data science Classification Support vector machine Outliers detection Feature selection mixed integer programming

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