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Thematische Bibliographien / Workforce Scheduling and Routing Problem / Zeitschriftenartikel

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Zeitschriftenartikel zum Thema „Workforce Scheduling and Routing Problem“

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Veröffentlicht am 25. Mai 2024

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1

Pereira, Dilson Lucas, Júlio César Alves, and Mayron César de Oliveira Moreira. "A multiperiod workforce scheduling and routing problem with dependent tasks." Computers & Operations Research 118 (June 2020): 104930. http://dx.doi.org/10.1016/j.cor.2020.104930.

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2

Punyakum, Voravee, Kanchana Sethanan, Krisanarach Nitisiri, and Rapeepan Pitakaso. "Hybrid Particle Swarm and Whale Optimization Algorithm for Multi-Visit and Multi-Period Dynamic Workforce Scheduling and Routing Problems." Mathematics 10, no. 19 (2022): 3663. http://dx.doi.org/10.3390/math10193663.

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This paper focuses on the dynamic workforce scheduling and routing problem for the maintenance work of harvesters in a sugarcane harvesting operation. Technician teams categorized as mechanical, hydraulic, and electrical teams are assumed to have different skills at different levels to perform services. The jobs are skill-constrained and have time windows. During a working day, a repair request from a sugarcane harvester may arrive, and as time passes, the harvester’s position may shift to other sugarcane fields. We formulated this problem as a multi-visit and multi-period dynamic workforce scheduling and routing problem (MMDWSRP) and our study is the first to address the workforce scheduling and routing problem (WSRP). A mixed-integer programming formulation and a hybrid particle swarm and whale optimization algorithm (HPSWOA) were firstly developed to solve the problem, with the objective of minimizing the total cost, including technician labor cost, penalty for late service, overtime, travel, and subcontracting costs. The HPSWOA was developed for route planning and maintenance work for each mechanical harvester to be provided by technician teams. The proposed algorithm (HPSWOA) was validated against Lingo computational software using numerical experiments in respect of static problems. It was also tested against the current practice, the traditional whale optimization algorithm (WOA), and traditional particle swarm optimization (PSO) in respect of dynamic problems. The computational results show that the HPSWOA yielded a solution with significantly better quality. The HPSWO was also tested against the traditional genetic algorithm (GA), bat algorithm (BA), WOA, and PSO to solve the well-known CEC 2017 benchmark functions. The computational results show that the HPSWOA achieved more superior performance in most cases compared to the GA, BA, WOA, and PSO algorithms.

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Xie, Fulin, Chris N. Potts, and Tolga Bektaş. "Iterated local search for workforce scheduling and routing problems." Journal of Heuristics 23, no. 6 (2017): 471–500. http://dx.doi.org/10.1007/s10732-017-9347-8.

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4

Algethami, Haneen, Anna Martínez-Gavara, and Dario Landa-Silva. "Adaptive multiple crossover genetic algorithm to solve workforce scheduling and routing problem." Journal of Heuristics 25, no. 4-5 (2018): 753–92. http://dx.doi.org/10.1007/s10732-018-9385-x.

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5

Castillo-Salazar, J. Arturo, Dario Landa-Silva, and Rong Qu. "Workforce scheduling and routing problems: literature survey and computational study." Annals of Operations Research 239, no. 1 (2014): 39–67. http://dx.doi.org/10.1007/s10479-014-1687-2.

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6

Urquhart, Neil, Emma Hart, and William Hutcheson. "Using MAP-Elites to support policy making around Workforce Scheduling and Routing." at - Automatisierungstechnik 68, no. 2 (2020): 110–17. http://dx.doi.org/10.1515/auto-2019-0107.

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AbstractAlgorithms such as MAP-Elites provide a means of allowing users to explore a solution space by returning an archive of high-performing solutions. Such an archive, can allow the user an overview of the solution space which may be useful when formulating policy around the problem itself. The number of solutions that can potentially be returned by MAP-Elites is controlled by a parameter d that discretises the user-defined features into ‘bins’. For a fixed evaluation budget, increasing the number of bins increases user-choice, but at the same time, may lead to a reduction in overall quality of solutions. We undertake a study of the application of Map-Elites to a Workforce Scheduling and Routing problem, using a set of realistic instances based in London.

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Fukunaga, Takashi, and Junko Hosoda. "Workforce scheduling and routing problem for maintenance work with various work condition on sites." Proceedings of Manufacturing Systems Division Conference 2022 (2022): 211. http://dx.doi.org/10.1299/jsmemsd.2022.211.

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8

Eliiyi, Uğur, Onur Uğurlu, and Sel Tatari. "A Sequential Workforce Scheduling and Routing Problem for the Retail Industry: A Case Study." Journal of Transportation and Logistics 7, no. 2 (2022): 479–98. http://dx.doi.org/10.26650/jtl.2022.1096085.

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9

Dahite, Lamiaa, Abdeslam Kadrani, Rachid Benmansour, Rym Nesrine Guibadj, and Cyril Fonlupt. "Multi-Objective Model and Variable Neighborhood Search Algorithms for the Joint Maintenance Scheduling and Workforce Routing Problem." Mathematics 10, no. 11 (2022): 1807. http://dx.doi.org/10.3390/math10111807.

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This paper addresses a problem faced by maintenance service providers: performing maintenance activities at the right time on geographically distributed machines subjected to random failures. This problem requires determining for each technician the sequence of maintenance operations to perform to minimize the total expected costs while ensuring a high level of machine availability. To date, research in this area has dealt with routing and maintenance schedules separately. This study aims to determine the optimal maintenance and routing plan simultaneously. A new bi-objective mathematical model that integrates both routing and maintenance considerations is proposed for time-based preventive maintenance. The first objective is to minimize the travel cost related to technicians’ routing. The second objective can either minimize the total preventive and corrective maintenance cost or the failure cost. New general variable neighborhood search (GVNS) and variable neighborhood descent (VND) algorithms based on the Pareto dominance concept are proposed and performed over newly generated instances. The efficiency of our approach is demonstrated through several experiments. Compared to the commercial solver and existing multi-objective VND and GVNS, these new algorithms obtain highly competitive results on both mono-objective and bi-objective variants.

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Çakırgil, Seray, Eda Yücel, and Gültekin Kuyzu. "An integrated solution approach for multi-objective, multi-skill workforce scheduling and routing problems." Computers & Operations Research 118 (June 2020): 104908. http://dx.doi.org/10.1016/j.cor.2020.104908.

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11

Alajkovic, Adrian, Mario Brcic, Viktorija Ivandic, Luka Bubalo, Mihael Koncic, and Mihael Kovac. "Delivery pattern planning in retailing with transport and warehouse workload balancing." Croatian operational research review 13, no. 1 (2022): 99–111. http://dx.doi.org/10.17535/crorr.2022.0007.

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Goods from warehouses must be scheduled in advance, prepared, routed, and delivered to shops. At least three systems directly interact within such a process: warehouse workforce scheduling, delivery scheduling, and routing system. Ideally, the whole problem with the preceding inventory management (restocking) would be solved in one optimization pass. In order to make the problem simpler, we first decompose the total problem by isolating the delivery scheduling. Then we connect the optimization model to the rest of the system by workload balancing goal that is a surrogate ofcoordination and criterion for the system robustness. This paper presents the practical application of top-down discrete optimization that streamlines operations and enables better reactivity to changes in circumstances. We search for repetitive weekly delivery patterns that balance the daily warehouse and transportation utilization in the absence of capacity constraints. Delivery patterns are optimized for the quality criteria regarding specific store-warehouse pair types, with a special focus on fresh food delivery that aims at reducing inventory write-offs due to aging. The previous setup included semimanual scheduling based on templates, historical prototypes, and domain knowledge. We have found that the system augmented with the new automated delivery scheduling system brings an improvement of 3% in the performance measure as well as speed in adjusting to the changes, such was the case with changes in policies during COVID-19 lockdowns.

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Punyakum, Voravee, Kanchana Sethanan, Krisanarach Nitisiri, Rapeepan Pitakaso, and Mitsuo Gen. "Hybrid differential evolution and particle swarm optimization for Multi-visit and Multi-period workforce scheduling and routing problems." Computers and Electronics in Agriculture 197 (June 2022): 106929. http://dx.doi.org/10.1016/j.compag.2022.106929.

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13

Novianto, Raditya, Suparno Suparno, Sutrisno Sutrisno, and Abdul Rahman. "APPLICATION OF NETWORK ANALYSIS CRASHING METHOD IN EVALUATING THE SCHEDULE OF NAVAL BASE FACILITY DEVELOPMENT PROJECT." JOURNAL ASRO 12, no. 01 (2021): 153. http://dx.doi.org/10.37875/asro.v12i01.392.

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A project of base facility is a kind of routine developing in Indonesian Naval. In this developmentt is necessary to develop methods in measuring performance and evaluating project time through a more accurate critical path feature. The research problem statement is how to evaluate the project schedule related to the time and cost of the Indonesian Navy's facility construction project by conducting a case study as a study for project scheduling at a later stage. The research objective is to identify the critical path of the project through network analysis, determine the factors that cause delays and how to overcome them, and calculate the time effectiveness and cost-efficiency of the project based on the calculation of scheduling acceleration. In this study, project performance measurement was carried out using the Earned Value Method (EVM) and network analysis using the Precedence Diagram Method (PDM). The solution to overcome delays with the crashing project method. The results of the discussion identified 15 critical path activities. The factor causing the delay is the delay in activities on the critical path due to the low level of productivity of the workforce group. The crashing method through additional 2 hours/day overtime can solve the problem of delays so that project implementation can be accelerated from the implementation of 256 working days to 226 working days (11.72% effectiveness) with the initial project cost of Rp. 74,316,727,585.00 reduced to Rp. 72,152,162,704.00 (2.91% efficiency). It will be measurable and reasonable in responsibility when it was suitable with the target.  Keywords : Network Analysis, Naval Base, and Project Development.

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Wang, Xu, and Jian Zhong. "An integrated optimization for minimizing the operation cost of home delivery services in O2O retail." International Journal of Industrial Engineering Computations 14, no. 2 (2023): 341–60. http://dx.doi.org/10.5267/j.ijiec.2022.12.005.

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During the spread of the epidemic, the home delivery service (HDS) has been quickly introduced by retailers which helps customers avoid the risk of viral infection while shopping at offline stores. However, the operation cost of HDS is a huge investment for O2O retailers. How to minimize the operating costs of HDS is an urgent issue for the industry. To solve this problem, we outline those management decisions of HDS that have an impact on operating costs, including dynamic vehicle routing, driver sizing and scheduling, and propose an integrated optimization model by comprehensively considering these management decisions. Moreover, the dynamic feature of online orders and the heterogeneous workforces are also considered in this model. To solve this model, an efficient adaptive large neighborhood search (ALNS) and branch-and-cut algorithms are developed. In the case study, we collected real data from a leading O2O retailer in China to assess the effectiveness of our proposed model and algorithms. Experimental results show that our approach can effectively reduce the operating costs of HDS. Furthermore, a comprehensive analysis is conducted to reveal the changing patterns in operating costs, and some valuable management insights are provided for O2O retailers. The theoretical and numerical results would shed light on the management of HDS for O2O retailers.

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Shao, Yufen, Jonathan F. Bard, and Ahmad I. Jarrah. "The therapist routing and scheduling problem." IIE Transactions 44, no. 10 (2012): 868–93. http://dx.doi.org/10.1080/0740817x.2012.665202.

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16

Pokutta, Sebastian, and Gautier Stauffer. "France Telecom workforce scheduling problem: a challenge." RAIRO - Operations Research 43, no. 4 (2009): 375–86. http://dx.doi.org/10.1051/ro/2009025.

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17

Shafahi, Ali, Zhongxiang Wang, and Ali Haghani. "Solving the School Bus Routing Problem by Maximizing Trip Compatibility." Transportation Research Record: Journal of the Transportation Research Board 2667, no. 1 (2017): 17–27. http://dx.doi.org/10.3141/2667-03.

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School bus planning is usually divided into routing and scheduling because of the complexity of solving them concurrently. However, the separation between these two steps may lead to worse solutions with higher overall costs than from solving them together. When the minimal number of trips in the routing problem is being determined, neglecting trip compatibility could increase the number of buses needed in the scheduling problem. This paper proposes a new formulation for the multischool homogeneous fleet routing problem that maximizes trip compatibility while minimizing total travel time. This plan incorporates the trip compatibility for the scheduling problem in the routing problem. A proposed heuristic algorithm for solving this problem decomposes the problem by schools. To compare the performance of the model with traditional routing problems, eight midsize data sets were generated. Importing the generated trips of the routing problems into the bus scheduling (blocking) problem shows that the proposed model can reduce the buses needed by up to 25%. A sensitivity analysis on coefficients of the model illustrates the effect of the weight of trip compatibility.

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L. van Eck, Maikel, Murat Firat, Wim P. M. Nuijten, Natalia Sidorova, and Wil M. P. van der Aalst. "Human Performance-Aware Scheduling and Routing of a Multi-Skilled Workforce." Complex Systems Informatics and Modeling Quarterly, no. 12 (October 31, 2017): 1–21. http://dx.doi.org/10.7250/csimq.2017-12.01.

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19

Goel, Asvin, and Frank Meisel. "Workforce routing and scheduling for electricity network maintenance with downtime minimization." European Journal of Operational Research 231, no. 1 (2013): 210–28. http://dx.doi.org/10.1016/j.ejor.2013.05.021.

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20

Li, Yan, Zhi Run Xiao, Wen Qing Dou, and Ying Yang. "A Constraint-Based Approach for Skilled Workforce Scheduling Problem." Applied Mechanics and Materials 536-537 (April 2014): 1669–73. http://dx.doi.org/10.4028/www.scientific.net/amm.536-537.1669.

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The Skilled Workforce Project Scheduling Problem (SWPSP) is a complex problem of task scheduling and resource assignment that comes up in the daily management of many company Service Centers. In this paper we present a constraint programming (CP) approach for the SWPSP. We extend the project scheduling literature by developing a project scheduling model that accounts for differing skills among workers. The computational results for the SWPSP show that the constraint programming approach increases the performance of the model solving processes. The results for the SWPSP is effective in solving the proposed problem.

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Li, Yan, Zhi Run Xiao, Wen Qing Dou, and Ying Yang. "A Constraint-Based Approach for Skilled Workforce Scheduling Problem." Applied Mechanics and Materials 631-632 (September 2014): 1295–99. http://dx.doi.org/10.4028/www.scientific.net/amm.631-632.1295.

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The Skilled Workforce Project Scheduling Problem (SWPSP) is a complex problem of task scheduling and resource assignment that comes up in the daily management of many company Service Centers. In this paper we present a constraint programming (CP) approach for the SWPSP. We extend the project scheduling literature by developing a project scheduling model that accounts for differing skills among workers. The computational results for the SWPSP show that the constraint programming approach increases the performance of the model solving processes. The results for the SWPSP is effective in solving the proposed problem.

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22

Becker, Tristan. "A decomposition heuristic for rotational workforce scheduling." Journal of Scheduling 23, no. 5 (2020): 539–54. http://dx.doi.org/10.1007/s10951-020-00659-2.

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Abstract In rotational workforce planning, a schedule is constructed from a sequence of work and rest periods. Each employee starts at a different part of the schedule, and after a certain amount of time, the schedule repeats. The length of the schedule increases with a higher number of employees. At the same time, various constraints on work sequences and days off have to be considered. For a large number of employees, it is difficult to construct a schedule that meets the requirements. It is important to ensure low solution times independently of the problem instance characteristics. In this work, a novel decomposition approach for rotational shift scheduling is proposed. The decomposition exploits the fact that most constraints in rotational workforce scheduling are imposed on the work shift sequence. By considering a fixed set of blocks to cover the demand, the problem complexity can be greatly reduced. Given a fixed set of blocks, we propose a network model that determines whether a feasible sequence of shift blocks exists. The decomposition approach is applied to the problem structure of the Rotating Workforce Scheduling Problem but may be extended to different problem structures. In a computational study, the decomposition approach is compared to a mathematical formulation and previous exact and heuristic approaches. Computational results show that the decomposition approach greatly outperforms previous heuristics on the standard benchmarks.

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Wu, Lingfang, and Xiaolin Xiang. "Emergency Resource Scheduling During COVID-19." E3S Web of Conferences 253 (2021): 01012. http://dx.doi.org/10.1051/e3sconf/202125301012.

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Due to the suddenness and uncertainty of the COVID-19, sufficient emergency resources should be allocated to the appropriate emergency space within a limited time. In order to ensure the smooth implementation of emergency resource scheduling, emergency resource must be timely and effectively supplied. Therefore, it is of great significance to study how to reasonably distribute emergency resource and how to optimize the vehicle routing problem to improve the efficiency of emergency. Based on the research of capacitated vehicle routing problem (CVRP) solved by traditional genetic algorithm, this paper proposes simulated annealing-genetic algorithm, which has been verified to effectively solve the capacitated vehicle routing problem.

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Rahardja, Untung, Fitri Andriyani, and Triyono Triyono. "Model Scheduling Optimization Workforce Management Marketing." Aptisi Transactions on Management (ATM) 4, no. 2 (2020): 92–100. http://dx.doi.org/10.33050/atm.v4i2.1259.

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This research focuses on completing workforce management marketing scheduling using genetic metaheuristic methods. Optimal scheduling to determine the duration of a job, the quality of employees, and meet the challenges to increase work scheduling targets according to marketing employee skills by maximizing operational time while providing satisfactory services to customers. Marketing employees increasingly rely on the right time to connect with their customers. The problem in this study considers marketing skills and activities to carry out work activities, namely promotion, follow-up, and stand-by in the office with the limitations of the existing workforce. This problem has the nature of NP-Hard so a quick solution requires the use of metaheuristic methods. The metaheuristic method was built in 11 constraints. The results show that the genetic metaheuristic method is capable of producing far better results. Therefore, employee scheduling is very important. This study aims to develop an optimization model for employee scheduling and to maximize operational time work. With this model, it is expected to achieve optimal scheduling for marketing management workforce.

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Lam, Edward, Pascal Van Hentenryck, and Phil Kilby. "Joint Vehicle and Crew Routing and Scheduling." Transportation Science 54, no. 2 (2020): 488–511. http://dx.doi.org/10.1287/trsc.2019.0907.

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Traditional vehicle routing problems implicitly assume that only one crew operates a vehicle for the entirety of its journey. However, this assumption is violated in many applications arising in humanitarian and military logistics. This paper considers a joint vehicle and crew routing and scheduling problem in which crews are able to interchange vehicles, resulting in space and time interdependencies between vehicle routes and crew routes. The problem is formulated as a mixed integer programming (MIP) model and a constraint programming (CP) model that overlay crew routing constraints over a standard vehicle routing problem. The constraint program uses a novel optimization constraint to detect infeasibility and to bound crew objectives. This paper also explores methods using large neighborhood search over the MIP and CP models. Experimental results indicate that modeling the vehicle and crew routing problems jointly and supporting vehicle interchanges for crews may bring significant benefits in cost reduction compared with a method that sequentializes these decisions.

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Suo, Long, Han Ma, Wanguo Jiao, and Xiaoming Liu. "Job-Deadline-Guarantee-Based Joint Flow Scheduling and Routing Scheme in Data Center Networks." Sensors 24, no. 1 (2023): 216. http://dx.doi.org/10.3390/s24010216.

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Many emerging Internet of Things (IoT) applications deployed on cloud platforms have strict latency requirements or deadline constraints, and thus meeting the deadlines is crucial to ensure the quality of service for users and the revenue for service providers in these delay-stringent IoT applications. Efficient flow scheduling in data center networks (DCNs) plays a major role in reducing the execution time of jobs and has garnered significant attention in recent years. However, only few studies have attempted to combine job-level flow scheduling and routing to guarantee meeting the deadlines of multi-stage jobs. In this paper, an efficient heuristic joint flow scheduling and routing (JFSR) scheme is proposed. First, targeting maximizing the number of jobs for which the deadlines have been met, we formulate the joint flow scheduling and routing optimization problem for multiple multi-stage jobs. Second, due to its mathematical intractability, this problem is decomposed into two sub-problems: inter-coflow scheduling and intra-coflow scheduling. In the first sub-problem, coflows from different jobs are scheduled according to their relative remaining times; in the second sub-problem, an iterative coflow scheduling and routing (ICSR) algorithm is designed to alternately optimize the routing path and bandwidth allocation for each scheduled coflow. Finally, simulation results demonstrate that the proposed JFSR scheme can significantly increase the number of jobs for which the deadlines have been met in DCNs.

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De Rosa, Barbara, Gennaro Improta, Gianpaolo Ghiani, and Roberto Musmanno. "The Arc Routing and Scheduling Problem with Transshipment." Transportation Science 36, no. 3 (2002): 301–13. http://dx.doi.org/10.1287/trsc.36.3.301.7832.

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28

Panggabean, Ellis Mardiana, Herman Mawengkang, Zainal Azis, and Rina Filia Sari. "Periodic Heterogeneous Vehicle Routing Problem With Driver Scheduling." IOP Conference Series: Materials Science and Engineering 300 (January 2018): 012017. http://dx.doi.org/10.1088/1757-899x/300/1/012017.

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29

Zhen, Lu, Jingwen Wu, Gilbert Laporte, and Zheyi Tan. "Heterogeneous instant delivery orders scheduling and routing problem." Computers & Operations Research 157 (September 2023): 106246. http://dx.doi.org/10.1016/j.cor.2023.106246.

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Popović, Vlado, Milorad Kilibarda, Milan Andrejić, Borut Jereb, and Dejan Dragan. "A New Sustainable Warehouse Management Approach for Workforce and Activities Scheduling." Sustainability 13, no. 4 (2021): 2021. http://dx.doi.org/10.3390/su13042021.

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Sustainable engineering is very important for logistics systems. Nowadays, sustainable warehouse management is a key factor in market success. Workforce fluctuation and inverting the number of customers’ demands make a lot of problems in distribution warehouses. This study addresses a sustainable approach for the workforce scheduling problem recognized in a real distribution warehouse. The problem arises from the high variability of demand for workers over one workday, which causes workforce surplus in some periods of the workday and shortages in others. Engineering managers of the distribution warehouse already use different full-time and part-time shifts, and schedule workers on different activities, but they still have significant workforce surpluses or shortages in some periods. This study proposes the scheduling of activities’ execution together with workers to face that variability and decrease the cost of the workforce. This idea comes from the fact that some activities in a distribution warehouse can be done in a specific time period after the need for them occurs. In this way, the variability of demand for workers can be decreased, and a lower workforce cost may be ensured. Based on this idea, the entire problem is modeled as integer linear programming. The real example of the problem is solved, and the proposed model is tested on randomly generated instances of the problem in Python by means of the PuLP linear programming package. The results indicate different positive effects in the manner of sustainable warehouse management: lower workforce costs, time savings, better utilization of all types of resources and equipment, increased employee satisfaction, and so on. For even 61% of instances of the introduced problem, the obtained cost of the workforce is lower by more than 20% if activities’ executions are scheduled together with employees.

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Liu, Ming, and Xin Liu. "Satisfaction-driven bi-objective multi-skill workforce scheduling problem." IFAC-PapersOnLine 52, no. 13 (2019): 229–34. http://dx.doi.org/10.1016/j.ifacol.2019.11.134.

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32

Ulusam Seçkiner, Serap, Hadi Gökçen, and Mustafa Kurt. "An integer programming model for hierarchical workforce scheduling problem." European Journal of Operational Research 183, no. 2 (2007): 694–99. http://dx.doi.org/10.1016/j.ejor.2006.10.030.

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Balakrishnan, Nagraj, and Richard T. Wong. "A network model for the rotating workforce scheduling problem." Networks 20, no. 1 (1990): 25–42. http://dx.doi.org/10.1002/net.3230200103.

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34

Díaz-Parra, Ocotlán, Jorge A. Ruiz-Vanoye, Beatriz Bernábe Loranca, Alejandro Fuentes-Penna, and Ricardo A. Barrera-Cámara. "A Survey of Transportation Problems." Journal of Applied Mathematics 2014 (2014): 1–17. http://dx.doi.org/10.1155/2014/848129.

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This paper aims at being a guide to understand the different types of transportation problems by presenting a survey of mathematical models and algorithms used to solve different types of transportation modes (ship, plane, train, bus, truck, Motorcycle, Cars, and others) by air, water, space, cables, tubes, and road. Some problems are as follows: bus scheduling problem, delivery problem, combining truck trip problem, open vehicle routing problem, helicopter routing problem, truck loading problem, truck dispatching problem, truck routing problem, truck transportation problem, vehicle routing problem and variants, convoy routing problem, railroad blocking problem (RBP), inventory routing problem (IRP), air traffic flow management problem (TFMP), cash transportation vehicle routing problem, and so forth.

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TAO, NING-RONG, ZU-HUA JIANG, and LU ZHEN. "SPATIAL SCHEDULING AND WORKFORCE ASSIGNMENT PROBLEM IN BLOCK ASSEMBLY SHOP OF SHIPBUILDING." Asia-Pacific Journal of Operational Research 31, no. 01 (2014): 1450006. http://dx.doi.org/10.1142/s0217595914500067.

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For shipbuilding, spatial scheduling and workforce assignment are two important issues for the operation management in block assembly shops. Spatial scheduling is to decide where and when to assemble blocks, while workforce assignment is to assign working teams to the blocks. Traditionally, they are made separately at different levels in the production management framework. The combining of such decisions presents additional complexity and new problems. This paper proposes an approach that solves jointly the spatial scheduling problem and the workforce assignment problem. The objective is to improve the coordination among working teams and increase the productivity of assembly shops. A spatial layout strategy is designed according to extreme point and deep bottom left strategies. By using genetic algorithm, a solution method is developed based on the spatial layout strategy and several assignment and sequence rules. Some computational experiments are conducted to evaluate the performance of the presented algorithm and compare it with other commonly used methods. Computational results validate the effectiveness and efficiency of the proposed algorithm.

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Li, Yulong, Chi Zhang, Chuanzhou Jia, Xiaodong Li, and Yimin Zhu. "Joint optimization of workforce scheduling and routing for restoring a disrupted critical infrastructure." Reliability Engineering & System Safety 191 (November 2019): 106551. http://dx.doi.org/10.1016/j.ress.2019.106551.

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GODWIN, T., RAM GOPALAN, and T. T. NARENDRAN. "FREIGHT TRAIN ROUTING AND SCHEDULING IN A PASSENGER RAIL NETWORK: COMPUTATIONAL COMPLEXITY AND THE STEPWISE DISPATCHING HEURISTIC." Asia-Pacific Journal of Operational Research 24, no. 04 (2007): 499–533. http://dx.doi.org/10.1142/s0217595907001358.

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In many countries, freight trains have to share a rail network with passenger trains. In this paper, we consider a situation where passenger trains must adhere to a strict published schedule, whereas freight train movements can be inserted at any convenient time, without disrupting scheduled passenger trains. We propose an algorithm for the problem of routing and scheduling of a single freight train in a passenger rail network. However, the multiple freight train routing and scheduling problem is shown to be NP-complete, even for simplified instances. Specifically, we show that both routing and scheduling of freight trains are difficult, even when only two freight trains are considered. It is also difficult when freight train movements are restricted to reach their destinations with no idling permitted at intermediate stations. We have developed a Stepwise Dispatching Heuristic for routing and scheduling multiple freight trains in a passenger rail network. Computational results confirm the efficacy of our algorithm for single freight train routing and of the proposed Stepwise Dispatching Heuristic.

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Fu, Jiawei, and Liang Ma. "Long-Haul Vehicle Routing and Scheduling with Biomathematical Fatigue Constraints." Transportation Science 56, no. 2 (2022): 404–35. http://dx.doi.org/10.1287/trsc.2021.1089.

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Hours of service (HOS) regulations are among the conventional safety constraints that are compiled by long-haul truck drivers. These regulations have been considered in models and algorithms of vehicle routing problems to assign safe schedules to drivers. However, the HOS regulations neglect a few crucial fatigue risk factors and, at times, fail to generate fatigue-reducing schedules. In this study, a set of biomathematical fatigue constraints (BFCs) derived from biomathematical models are considered for a long-haul vehicle routing and scheduling problem. A BFC scheduling algorithm and a BFC-HOS scheduling algorithm have been developed and then embedded within a tabu search heuristic to solve the combined vehicle routing and scheduling problem. All the solution methods have been tested on modified Solomon instances and a real-life instance, and the computational results confirm the advantages of employing a sophisticated and fatigue-reducing scheduling procedure when planning long-haul transportation.

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Ghoseiri, K., and S. F. Ghannad. "Hybrid Genetic Algorithm for Vehicle Routing and Scheduling Problem." Journal of Applied Sciences 9, no. 1 (2008): 79–87. http://dx.doi.org/10.3923/jas.2009.79.87.

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40

Pekel, Engin. "Deep Learning Approach to Technician Routing and Scheduling Problem." ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal 11, no. 2 (2022): 191–206. http://dx.doi.org/10.14201/adcaij.27393.

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This paper proposes a hybrid algorithm including the Adam algorithm and body change operator (BCO). Feasible solutions to technician routing and scheduling problems (TRSP) are investigated by performing deep learning based on the Adam algorithm and the hybridization of Adam-BCO. TRSP is a problem where all tasks are routed, and technicians are scheduled. In the deep learning method based on the Adam algorithm and Adam-BCO algorithm, the weights of the network are updated, and these weights are evaluated as Greedy approach, and routing and scheduling are performed. The performance of the Adam-BCO algorithm is experimentally compared with the Adam and BCO algorithm by solving the TRSP on the instances developed from the literature. The numerical results evidence that Adam-BCO offers faster and better solutions considering Adam and BCO algorithm. The average solution time increases from 0.14 minutes to 4.03 minutes, but in return, Gap decreases from 9.99% to 5.71%. The hybridization of both algorithms through deep learning provides an effective and feasible solution, as evidenced by the results.

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Pajoutan, Mojdeh, Amirmohsen Golmohammadi, and Mehdi Seifbarghy. "CMS scheduling problem considering material handling and routing flexibility." International Journal of Advanced Manufacturing Technology 72, no. 5-8 (2014): 881–93. http://dx.doi.org/10.1007/s00170-014-5696-8.

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Bögl, Michael, Karl F. Doerner, and Sophie N. Parragh. "The school bus routing and scheduling problem with transfers." Networks 65, no. 2 (2015): 180–203. http://dx.doi.org/10.1002/net.21589.

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43

Sousa Matos, Marcos Raylan, Yuri Frota, and Luiz Satoru Ochi. "Green Vehicle Routing and Scheduling Problem with Split Delivery." Electronic Notes in Discrete Mathematics 69 (August 2018): 13–20. http://dx.doi.org/10.1016/j.endm.2018.07.003.

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Rastegar, Mahsa, Hossein Karimi, and Hashem Vahdani. "Technicians scheduling and routing problem for elevators preventive maintenance." Expert Systems with Applications 235 (January 2024): 121133. http://dx.doi.org/10.1016/j.eswa.2023.121133.

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Jin, Zhilin. "Home Health Care Problem Related to Routing and Scheduling." Frontiers in Business, Economics and Management 9, no. 2 (2023): 240–42. http://dx.doi.org/10.54097/fbem.v9i2.9290.

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Home Health Care (HHC) is a form of nursing that provides medical and non-medical health services to patients in their places of residence. It aims to help individuals who require treatment, monitoring, or recovery to receive professional medical services in the comfort of their homes. The purpose of this paper is to propose a literature survey on HHC dealing with routing and scheduling and some discussions on current trends with a focus on the medical resource aspects.

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Chevroton, Hugo, Yannick Kergosien, Lotte Berghman, and Jean-Charles Billaut. "Solving an integrated scheduling and routing problem with inventory, routing and penalty costs." European Journal of Operational Research 294, no. 2 (2021): 571–89. http://dx.doi.org/10.1016/j.ejor.2021.02.012.

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Kletzander, Lucas, Nysret Musliu, Johannes Gärtner, Thomas Krennwallner, and Werner Schafhauser. "Exact Methods for Extended Rotating Workforce Scheduling Problems." Proceedings of the International Conference on Automated Planning and Scheduling 29 (May 25, 2021): 519–27. http://dx.doi.org/10.1609/icaps.v29i1.3518.

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In many professions daily demand for different shifts varies during the week. The rotating workforce scheduling problem deals with the creation of repeating schedules for such demand and is therefore of high practical relevance. This paper investigates solving this real-life problem with several new practically relevant features. This includes early recognition of certain infeasibility criteria, complex rest time constraints regarding weekly rest time, and optimization goals to deal with optimal assignments of free weekends. We introduce a state-of-the-art constraint model and evaluate it with different extensions. The evaluation shows that many real-life instances can be solved to optimality using a constraint solver. Our approach is under deployment in a state-of-the-art commercial solver for rotating workforce scheduling.

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Zhang, Yu, Mengze Cui, and Sergei Gorlatch. "An adaptive scheduling routing for multimedia services based on software-defined networks." ITM Web of Conferences 45 (2022): 01002. http://dx.doi.org/10.1051/itmconf/20224501002.

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We address the routing optimization problem in Software-Defined Networks (SDN) while satisfying multiple QoS constraints of multimedia services. In this paper, we 1) formally define the problem of routing optimization in SDN under multiple QoS constraints, and 2) suggest a novel architecture based on SDN for providing QoS services in the network. We propose an adaptive scheduling routing optimization approach in SDN that improves the classical Dijkstra routing algorithm. We report the results of experiments using the Mininet simulation framework that confirm the advantages of our proposed QoS routing optimization approach as compared to the state-of-the-art solutions.

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Rijal, Arpan, Marco Bijvank, Asvin Goel, and René de Koster. "Workforce Scheduling with Order-Picking Assignments in Distribution Facilities." Transportation Science 55, no. 3 (2021): 725–46. http://dx.doi.org/10.1287/trsc.2020.1029.

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Scheduling the availability of order pickers is crucial for effective operations in a distribution facility with manual order pickers. When order-picking activities can only be performed in specific time windows, it is essential to jointly solve the order picker shift scheduling problem and the order picker planning problem of assigning and sequencing individual orders to order pickers. This requires decisions regarding the number of order pickers to schedule, shift start and end times, break times, as well as the assignment and timing of order-picking activities. We call this the order picker scheduling problem and present two formulations. A branch-and-price algorithm and a metaheuristic are developed to solve the problem. Numerical experiments illustrate that the metaheuristic finds near-optimal solutions at 80% shorter computation times. A case study at the largest supermarket chain in The Netherlands shows the applicability of the solution approach in a real-life business application. In particular, different shift structures are analyzed, and it is concluded that the retailer can increase the minimum compensated duration for employed workers from six hours to seven or eight hours while reducing the average labor cost with up to 5% savings when a 15-minute flexibility is implemented in the scheduling of break times.

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Majidi, Ali, Pedram Farghadani-Chaharsooghi, and S. Mohammad J. Mirzapour Al-e-Hashem. "Sustainable Pricing-Production-Workforce-Routing Problem for Perishable Products by Considering Demand Uncertainty; A Case Study from the Dairy Industry." Transportation Journal 61, no. 1 (2022): 60–102. http://dx.doi.org/10.5325/transportationj.61.1.0060.

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Abstract The production routing problem seeks to simultaneously optimize production, routing, and inventory decisions for the plant and the suppliers. In this article an integrated multi-objective sustainable pricing-production-workforce-routing problem is presented for perishable products. Total profit, workforce planning, and vehicle fuel consumption are considered as objective functions due to the importance of operational performance, social, and environmental concerns. The application of the proposed approach is investigated using real case data from a dairy product supply chain. Furthermore, a new solution approach, called Fuzzy Domination Self-Learning Non-Dominated Sorting Algorithm (FDSL-NSGA-II), is developed to solve the problem. The results show that the Pareto solutions of FDSL-NSGA-II outperform those of the classic NSGA-II. Moreover, the findings show that the proposed model can create a surpassing tradeoff between the various aspects of a supply chain, including production, distribution, and workforce planning. In addition, it concurrently optimizes the selling price and protects the environment from the negative impacts of greenhouse gas emissions (GHGs). A comprehensive analysis of the results reveals several managerial insights for decision makers in the logistics industry.

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