Relevant bibliographies by topics / Workforce Scheduling and Routing Problem

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  1. Journal articles
  2. Dissertations / Theses
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  4. Book chapters
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Academic literature on the topic 'Workforce Scheduling and Routing Problem'

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Published: 25 May 2024

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Journal articles on the topic "Workforce Scheduling and Routing Problem"

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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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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 (October 6, 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 (July 18, 2017): 471–500. http://dx.doi.org/10.1007/s10732-017-9347-8.

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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 (August 2, 2018): 753–92. http://dx.doi.org/10.1007/s10732-018-9385-x.

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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 (August 14, 2014): 39–67. http://dx.doi.org/10.1007/s10479-014-1687-2.

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Urquhart, Neil, Emma Hart, and William Hutcheson. "Using MAP-Elites to support policy making around Workforce Scheduling and Routing." at - Automatisierungstechnik 68, no. 2 (February 25, 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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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 (December 30, 2022): 479–98. http://dx.doi.org/10.26650/jtl.2022.1096085.

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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 (May 25, 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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Dissertations / Theses on the topic "Workforce Scheduling and Routing Problem"

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Algethami, Haneen. "Genetic algorithms for workforce scheduling and routing problem." Thesis, University of Nottingham, 2017. http://eprints.nottingham.ac.uk/47712/.

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The Workforce Scheduling and Routing Problem (WSRP) is described as the assignment of personnel to visits across various geographical locations. Solving this problem demands tackling scheduling and routing constraints while aiming to minimise the total operational cost. With current computational capabilities, small WSRPs are solvable using exact methods. However, it is difficult to solve when they are larger. The difficulty of WSRP is further increased when processing conflicting assignments or dealing with workers unavailability at customer's areas. Genetic Algorithms (GAs) have proved their effectiveness in these regards, because of their search capability to acquire good solutions in a reasonable computational time. A GA consists of many components, which can be chosen and combined in numerous procedures. In the case of solving scheduling and routing problems separately, different GAs have been proposed. When solving WSRP problem instances, it has been quite common to use the design components, intended for scheduling or routing problems. In this thesis, 42 real-world Home Health Care (HHC) planning problem datasets are used as instances of the WSRP. Different GA components are presented in this study, tailored for the combined settings. This has made major contributions to understanding how GAs works in a challenging real-world problem. Research interests in this work are categorised into two parts. The first part aims to understand how to employ different genetic operators effectively when solving WSRPs. The work intends to design and select the best combination of components that provide good solutions. Accordingly, seven well-known crossovers, three mutation operators and eight cost-based operators are implemented. In addition, two repair heuristics to tackle infeasibility. Nevertheless, a direct chromosome representation has resulted in poor solutions. Thus, there is a need for more tailored components for this problem. Therefore, an indirect chromosome representation, designed specifically to tackle WSRPs, is presented. The aim is to ensure initial solutions feasibility. Due to the quality of solutions, the GA introduced is considered an effective baseline evolutionary algorithm for WSRP. This work also suggested that each problem set requires different parameter settings. The second research interest intends to increase the GA efficiency. One approach is to investigate the effect of using adaptive components on the quality of WSRPs solutions. The aim is to adaptively alter parameter values instead of tuning an algorithm to a specific instance. Three aspects are adjusted during the run according to different rules: operator rates, population size, and crossover operator function. Thus, six variations of a diversity-based adaptive GA is presented. Not only the adaptive GA has improved the results, especially for large WSRP scenarios, but also it reduces the computational time. Another aspect investigated is the effect of using a group of crossover operators rather than using one operator throughout the search. Six crossover operators, well known and problem-specific are used as part of a multiple crossover GA framework. To evaluate an operator effectiveness, a reinforcement-learning model is developed with three performance measurements. The most successful variant of this algorithm finds the best-known results for the larger problem instances and matching the best-known results for some of the smaller ones. When combining this method with the adaptive GA, it provided some of the best results, as compared to established algorithms. The presented methods have contributed in reducing the operational costs for this constrained combinatorial optimisation problem.
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Laesanklang, Wasakorn. "Heuristic decomposition and mathematical programming for workforce scheduling and routing problems." Thesis, University of Nottingham, 2017. http://eprints.nottingham.ac.uk/39883/.

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This thesis presents a PhD research project using a mathematical programming approach to solve a home healthcare problem (HHC) as well as general workforce scheduling and routing problems (WSRPs). In general, the workforce scheduling and routing problem consists of producing a schedule for mobile workers to make visits at different locations in order to perform some tasks. In some cases, visits may have time-wise dependencies in which a visit must be made within a time period depending on the other visit. A home healthcare problem is a variant of workforce scheduling and routing problems, which consists in producing a daily schedule for nurses or care workers to visit patients at their home. The scheduler must select qualified workers to make visits and route them throughout the time horizon. We implement a mixed integer programming model to solve the HHC. The model is an adaptation of the WSRP from the literature. However, the MIP solver cannot solve a large-scale real-world problem defined in this model form because the problem requires large amounts of memory and computational time. To tackle the problem, we propose heuristic decomposition approaches which split a main problem into sub-problems heuristically and each sub-problem is solved to optimality by the MIP solver. The first decomposition approach is a geographical decomposition with conflict avoidance (GDCA). The algorithm avoids conflicting assignments by solving sub-problems in a sequence in which worker's availabilities are updated after a sub-problem is solved. The approach can find a feasible solution for every HHC problem instance tackled in this thesis. The second approach is a decomposition with conflict repair and we propose two variants: geographical decomposition with conflict repair (GDCR) and repeated decomposition and conflict repair (RDCR). The GDCR works in the same way as GDCA but instead of solving sub-problems in a given sequence, they are solved with no specific order and conflicting assignments are allowed. Later on, the conflicting assignments are resolved by a conflicting assignments repair process. The remaining unassigned visits are allocated by a heuristic assignment algorithm. The second variant, RDCR, tackles the unassigned visits by repeating the decomposition and conflict repair until no further improvement has been found. We also conduct an experiment to use different decomposition rules for RDCR. Based on computational experiments conducted in this thesis, the RDCR is found to be the best of the heuristic decomposition approaches. Therefore, the RDCR is extended to solve a WSRP with time-dependent activities constraints. The approach requires modification to accommodate the time-dependent activities constraints which means that two visits may have time-wise requirements such as synchronisation, time overlapped, etc. In addition, we propose a reformulated MIP model to solve the HHC problem. The new model is considered to be a compact model because it has significantly fewer constraints. The aim of the reformulation is to reduce the solver requirements for memory and computational time. The MIP solver can solve all the HHC instances formulated in a compact model. Most of solutions obtained with this approach are the best known solutions so far except for those the instances for which the optimal solution can be found using the full MIP model. Typically, this approach requires computational time below one hour per instance. This problem reformulation is so far the best approach to solve the HHC instances considered in this thesis. The heuristic decomposition and model reformulation proposed in this thesis can find solutions to the real-world home healthcare problem. The main achievement is the reduction of computational memory and computational time which are required by the optimisation solver. Our studies show the best way to control the use of solver memory is the heuristic decomposition approach, particularly the RDCR method. The RDCR method can find a solution for every instance used throughout this thesis and keep the memory usage within personal computer memory ranges. Also, the computational time required to solve an instance being less than 8 minutes, for which the solution gap to the optimal solution is on average 12%. In contrast, the strong point of the model reformulation approach over the heuristic decomposition is that the model reformulation provides higher quality solutions. The relative gaps of solutions between the solution for solving the reformulated model and the solution from solving the full model is less than 1% whilst its the computational time could be up to one hour and its computational memory could require up to 100 GB. Therefore, the heuristic decomposition approach is a method for finding a solution using restricted resources while the model reformulation is an approach for when a high solution quality is required. Hence, two mathematical programming based heuristic approaches are each more suitable in different circumstances in which both find high quality solutions within an acceptable time limit.
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Lerouge, Mathieu. "Designing and generating user-centered explanations about solutions of a Workforce Scheduling and Routing Problem." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPAST174.

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Les systèmes d'aide à la décision basés sur l'optimisation combinatoire trouvent des applications dans divers domaines professionnels. Cependant, les décideurs qui utilisent ces systèmes ne comprennent souvent pas les concepts mathématiques et les principes algorithmiques qui les sous-tendent. Ce manque de compréhension peut entraîner du scepticisme et une réticence à accepter les solutions générées par le système, érodant ainsi la confiance placée dans le système. Cette thèse traite cette problématique dans le cas du problème de planification d'employés mobiles, en anglais Workforce Scheduling and Routing Problem (WSRP), un problème d'optimisation combinatoire couplant de l'allocation de ressources humaines et du routage.Tout d'abord, nous proposons un cadre qui modélise le processus d'explication de solutions pour les utilisateurs d'un système de résolution de WSRP, permettant d'aborder une large gamme de sujets. Les utilisateurs initient le processus en faisant des observations sur une solution et en formulant des questions liées à ces observations grâce à des modèles de texte prédéfinis. Ces questions peuvent être de type contrastif, scénario ou contrefactuel. D'un point de vue mathématique, elles reviennent essentiellement à se demander s'il existe une solution faisable et meilleure dans un voisinage de la solution courante. Selon les types de questions, cela conduit à la formulation d'un ou de plusieurs problèmes de décision et de programmes mathématiques.Ensuite, nous développons une méthode pour générer des textes d'explication de différents types, avec un vocabulaire de haut niveau adapté aux utilisateurs. Notre méthode repose sur des algorithmes efficaces calculant du contenu explicatif afin de remplir des modèles de textes d'explication. Des expériences numériques montrent que ces algorithmes ont des temps d'exécution globalement compatibles avec une utilisation en temps quasi-réel des explications par les utilisateurs.Enfin, nous présentons un design de système structurant les interactions entre nos techniques de génération d'explications et les utilisateurs qui reçoivent les textes d'explication. Ce système sert de base à un prototype d'interface graphique visant à démontrer l'applicabilité pratique et les potentiels bénéfices de notre approche dans son ensemble
Decision support systems based on combinatorial optimization find application in various professional domains. However, decision-makers who use these systems often lack understanding of their underlying mathematical concepts and algorithmic principles. This knowledge gap can lead to skepticism and reluctance in accepting system-generated solutions, thereby eroding trust in the system. This thesis addresses this issue in the case of the Workforce Scheduling and Routing Problems (WSRP), a combinatorial optimization problem involving human resource allocation and routing decisions.First, we propose a framework that models the process for explaining solutions to the end-users of a WSRP-solving system while allowing to address a wide range of topics. End-users initiate the process by making observations about a solution and formulating questions related to these observations using predefined template texts. These questions may be of contrastive, scenario or counterfactual type. From a mathematical point of view, they basically amount to asking whether there exists a feasible and better solution in a given neighborhood of the current solution. Depending on the question types, this leads to the formulation of one or several decision problems and mathematical programs.Then, we develop a method for generating explanation texts of different types, with a high-level vocabulary adapted to the end-users. Our method relies on efficient algorithms for computing and extracting the relevant explanatory information and populates explanation template texts. Numerical experiments show that these algorithms have execution times that are mostly compatible with near-real-time use of explanations by end-users. Finally, we introduce a system design for structuring the interactions between our explanation-generation techniques and the end-users who receive the explanation texts. This system serves as a basis for a graphical-user-interface prototype which aims at demonstrating the practical applicability and potential benefits of our approach
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Xie, Fulin. "Models and algorithms for workforce scheduling and routing problems in emergency response services." Thesis, University of Southampton, 2018. https://eprints.soton.ac.uk/422176/.

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Emergency response services play a key role in protecting public safety and health, and therefore developing effective and efficient response systems is of critical importance. In this thesis, we focus on the workforce scheduling and routing problems (WSRPs) that are commonly faced by emergency response organisations. We first present a simulation model for real-time emergency vehicle dispatching and routing, developed based on a case study of a British company providing emergency road services. The developed model is used to evaluate system performance, test scenarios and compare the effectiveness of different dispatching policies. The results of simulation study motivate us to design more advanced heuristic algorithms for the static WSRP. To this purpose, we develop a simple and fast algorithm based on the iterated local search (ILS) framework. The performance of the proposed algorithm is evaluated on benchmark instances against an off-the-shelf optimizer and an existing adaptive large neighbourhood search algorithm. The proposed ILS algorithm is also applied to solve the skill vehicle routing problem, which can be viewed as a special case of the WSRP. To further improve the decision making, we exploit the stochastic information about future requests and integrate this part of information into the solution method for the dynamic WSRP. A stochastic set-partitioning model is described and integrated with a sampling-based approach. The proposed model uses a two-stage framework, where the first-stage is concerned with finding a set of feasible routes covering known requests, while the second-stage estimates the effect of the same routes with respect to future requests. The performance of the proposed model is evaluated against a deterministic model and a naive greedy heuristic within a simulation framework.
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Fransson, Rasmus, and Michael Janfjord. "Online Workforce Scheduling and Routing : A case study at an on-site service provider." Thesis, Luleå tekniska universitet, Institutionen för ekonomi, teknik och samhälle, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-64125.

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The consumer market of today is characterized by emphasis on superior customer satisfaction and personalization of services. This entails higher customer expectations on organizations, which also includes the workforce scheduling processes in which the consumers expect more decision-power to dictate what they want, when and where they want services to be delivered. For organizations that deliver on-site services, the routing aspect becomes an important part of the scheduling process. Literature on Workforce Scheduling and Routing Problems (WSRP) seldom relate to characteristics of the more dynamic consumer market. As the markets and consumer needs become more flexible, the relevance for research concerning these characteristics increases. This study addresses this by reviewing current literature and present common solution methodologies applied to WSRP, as well as the effects of the online scheduling characteristics. With this as a foundation, a discussion is provided of how WSRP and online scheduling can be combined in order to improve resource utilization and minimize travel time for an on-site service provider. The overall aim of the study is to investigate how an online WSRP with exact time windows can be formulated and solved. The result is a four-stage hybrid method including linear integer programming and constructive heuristics with the objective to minimize travel time, idle time, and the makespan in the schedules. A case study has been conducted on an on-site service provider, and by applying the proposed hybrid methodology on the case company’s scheduling process, results have been obtained that demonstrates improvements of travel time and resource utilization. The study also demonstrate that the appliance of flexible travel times and product dependent service times have positive impact on the quality of the generated schedules. A key insight is that organizations working with exact time windows have to be aware of the trade-off between customer preferences and operational efficiency in day-to-day operations. Thus, organizations have to decide what holds most importance to the organization’s long-term success.
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Castillo, Salazar José Arturo. "Optimisation models and algorithms for workforce scheduling and routing." Thesis, University of Nottingham, 2015. http://eprints.nottingham.ac.uk/30886/.

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This thesis investigates the problem of scheduling and routing employees that are required to perform activities at clients’ locations. Clients request the activities to be performed during a time period. Employees are required to have the skills and qualifications necessary to perform their designated activities. The working time of employees must be respected. Activities could require more than one employee. Additionally, an activity might have time-dependent constraints with other activities. Time-dependent activities constraints include: synchronisation, when two activities need to start at the same time; overlap, if at any time two activities are being performed simultaneously; and with a time difference between the start of the two activities. Such time difference can be given as a minimum time difference, maximum time difference, or a combination of both (min-max). The applicability of such workforce scheduling and routing problem (WSRP) is found in many industries e.g. home health care provision, midwives visiting future mothers, technicians performing installations and repairs, estate agents showing residences for sale, security guards patrolling different locations, etc. Such diversity makes the WSRP an important combinatorial optimisation problem to study. Five data sets, obtained from the literature, were normalised and used to investigate the problem. A total of 375 instances were derived from these data sets. Two mathematical models, an integer and a mixed integer, are used. The integer model does not consider the case when the number of employees is not enough to perform all activities. The mixed integer model can leave activities unassigned. A mathematical solver is used to obtain feasible solutions for the instances. The solver provides optimal solutions for small instances, but it cannot provide feasible solutions for medium and large instances. This thesis presents the gradual development of a greedy heuristic that is designed to tackle medium and large instances. Five versions of the greedy heuristic are presented, each of them obtains better results than the previous one. All versions are compared to the results obtained by the mathematical solver when using the mixed integer model. The greedy heuristic exploits domain information to speed the search and discard infeasible solutions. It uses tailored functions to deal with each of the time-dependent activity constraints. These constraints make more difficult the solution process. Further improvements are obtained by using tabu search. It provides moves based on the tailored functions of the greedy heuristic. Overall, the greedy heuristic and the tabu search, maintain feasible solutions at all times. The main contributions of this thesis are: the definition of WSRP; the introduction of 375 instances based on five data sets; the adaptation of two mathematical models; the introduction of a greedy heuristic capable of obtaining better results than the solver; and, the implementation of a tabu search to further improve the results.
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Al-Hamad, Khaled. "Tabu search for ship routing and scheduling." Thesis, Brunel University, 2006. http://bura.brunel.ac.uk/handle/2438/5071.

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This thesis examines exact and heuristic approaches to solve the Ship Routing and Scheduling Problem (SRSP). The method was developed to address the problem of loading cargos for many customers using heterogeneous vessels. Constraints relate to delivery time windows imposed by customers, the time horizon by which all deliveries must be made and vessel capacities. The objective is to minimise the overall operation cost, where all customers are satisfied. Two types of routing and scheduling are considered, one called single-cargo problem, where only one cargo can be loaded into a ship, and the second type called multi-cargo problem, where multiple products can be carried on a ship to be delivered to different customers. The exact approach comprises two stages. In the first stage, a number of candidate feasible schedules is generated for each ship in the fleet. The second stage is to model the problem as a set partitioning problem (SPP) where the columns are the candidate feasible schedules obtained in the first stage. The heuristic approach uses Tabu Search (TS). Most of the TS operations, such as insert and swap moves, tenure, tabu list, intensification, and diversification are used. The results of a computational investigation are presented. Solution quality and execution time are explored with respect to problem size and parameters controlling the tabu search such as tenure and neighbourhood size. The results showed that the average of the solution gap between TS solution and SPP solution is up to 28% (for small problems) and up to 18% for large problems. However, obtaining an optimal solution requires a large amount of computer time to produce the solution compared to obtaining approximate solutions using the TS approach. The use of Tabu Search for SRSP is novel and the results indicate that it is viable approach for large problems.
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Bögl, Michael, Karl Doerner, and Sophie N. Parragh. "The School Bus Routing and Scheduling Problem with Transfers." Wiley Periodicals, Inc, 2015. http://dx.doi.org/10.1002/net.21589.

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In this article, we study the school bus routing and scheduling problem with transfers arising in the field of nonperiodic public transportation systems. It deals with the transportation of pupils from home to their school in the morning taking the possibility that pupils may change buses into account. Allowing transfers has several consequences. On the one hand, it allows more flexibility in the bus network structure and can, therefore, help to reduce operating costs. On the other hand, transfers have an impact on the service level: the perceived service quality is lower due to the existence of transfers; however, at the same time, user ride times may be reduced and, thus, transfers may also have a positive impact on service quality. The main objective is the minimization of the total operating costs. We develop a heuristic solution framework to solve this problem and compare it with two solution concepts that do not consider transfers. The impact of transfers on the service level in terms of time loss (or user ride time) and the number of transfers is analyzed. Our results show that allowing transfers reduces total operating costs significantly while average and maximum user ride times are comparable to solutions without transfers. (authors' abstract)
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Cowling, Peter I., N. J. Colledge, Keshav P. Dahal, and Stephen M. Remde. "The trade off between diversity and quality for multi-objective workforce scheduling." Springer-Verlag, 2006. http://hdl.handle.net/10454/2511.

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In this paper we investigate and compare multi-objective and weighted single objective approaches to a real world workforce scheduling problem. For this difficult problem we consider the trade off in solution quality versus population diversity, for different sets of fixed objective weights. Our real-world workforce scheduling problem consists of assigning resources with the appropriate skills to geographically dispersed task locations while satisfying time window constraints. The problem is NP-Hard and contains the Resource Constrained Project Scheduling Problem (RCPSP) as a sub problem. We investigate a genetic algorithm and serial schedule generation scheme together with various multi-objective approaches. We show that multi-objective genetic algorithms can create solutions whose fitness is within 2% of genetic algorithms using weighted sum objectives even though the multi-objective approaches know nothing of the weights. The result is highly significant for complex real-world problems where objective weights are seldom known in advance since it suggests that a multi-objective approach can generate a solution close to the user preferred one without having knowledge of user preferences.
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Yuan, Lufeng. "A Heuristic Approach for the Home Health Care Scheduling and Routing Problem." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/41277.

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Abstract Home Health Care (HHC) is a health care service delivered by sending caregivers such as nurses or personal support workers (PSW) to visit patients in their homes. The assignment of patients to nurses as well as the sequencing of patients for each nurse is called the Home Health Care Scheduling and Routing Problem (HHCSRP). This thesis proposes a heuristic approach to solve HHCSRP to which it is hard and even impossible to obtain an optimal solution for relative larger instances in a reasonable amount of computational time by using an exact algorithm as HHCSRP is NP hard. In the approach, this thesis developed and contributed a heuristic partition method to partition patients into a number of single nurse groups. The computational test result shows that the proposed approach can achieve good solutions which remain within 5% of the commercial solver CPLEX’s best solution using an acceptable solution time on all test instances.
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Books on the topic "Workforce Scheduling and Routing Problem"

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Subtour-Eliminations-Verfahren zur Lösung asymmetrischer Routing-Probleme. Göttingen: Vandenhoeck & Ruprecht, 1991.

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On method and system design for a problem in vehicle routing and scheduling. Lappeenranta: Lappeenranta University of Technology, 1987.

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Weiss, Illa. The Resource Transfer Problem: A Framework for Integrated Scheduling and Routing Problems. Springer, 2018.

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A Group Theoretic Tabu Search Methodology for Solving the Theater Distribution Vehicle Routing and Scheduling Problem. Storming Media, 2002.

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Book chapters on the topic "Workforce Scheduling and Routing Problem"

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Pinheiro, Rodrigo Lankaites, Dario Landa-Silva, and Jason Atkin. "A Variable Neighbourhood Search for the Workforce Scheduling and Routing Problem." In Advances in Intelligent Systems and Computing, 247–59. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27400-3_22.

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Gu, Hanyu, Yefei Zhang, and Yakov Zinder. "Lagrangian Relaxation in Iterated Local Search for the Workforce Scheduling and Routing Problem." In Lecture Notes in Computer Science, 527–40. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34029-2_34.

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Urquhart, Neil, and Emma Hart. "Optimisation and Illumination of a Real-World Workforce Scheduling and Routing Application (WSRP) via Map-Elites." In Parallel Problem Solving from Nature – PPSN XV, 488–99. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99253-2_39.

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Laesanklang, Wasakorn, Rodrigo Lankaites Pinheiro, Haneen Algethami, and Dario Landa-Silva. "Extended Decomposition for Mixed Integer Programming to Solve a Workforce Scheduling and Routing Problem." In Operations Research and Enterprise Systems, 191–211. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27680-9_12.

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Urquhart, Neil, Emma Hart, and William Hutcheson. "Quantifying the Effects of Increasing User Choice in MAP-Elites Applied to a Workforce Scheduling and Routing Problem." In Applications of Evolutionary Computation, 49–63. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16692-2_4.

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Holtvogt, Nadine. "Crew Scheduling Optimization." In The Service Routing Problem, 61–76. Wiesbaden: Springer Fachmedien Wiesbaden, 2011. http://dx.doi.org/10.1007/978-3-658-24126-1_3.

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Holtvogt, Nadine. "Routing and Scheduling Problems." In The Service Routing Problem, 9–59. Wiesbaden: Springer Fachmedien Wiesbaden, 2011. http://dx.doi.org/10.1007/978-3-658-24126-1_2.

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Holtvogt, Nadine. "Crew Scheduling and Shifting Module." In The Service Routing Problem, 95–123. Wiesbaden: Springer Fachmedien Wiesbaden, 2011. http://dx.doi.org/10.1007/978-3-658-24126-1_6.

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Spada, Michela, Michel Bierlaire, and Thomas M. Liebling. "School Bus Routing and Scheduling Problem." In Operations Research Proceedings 2002, 180–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-642-55537-4_29.

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Goel, Asvin, Volker Gruhn, and Thomas Richter. "Mobile Workforce Scheduling Problem with Multitask-Processes." In Business Process Management Workshops, 81–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12186-9_9.

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Conference papers on the topic "Workforce Scheduling and Routing Problem"

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Algethami, Haneen, Rodrigo Lankaites Pinheiro, and Dario Landa-Silva. "A genetic algorithm for a workforce scheduling and routing problem." In 2016 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2016. http://dx.doi.org/10.1109/cec.2016.7743889.

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"Computational Study for Workforce Scheduling and Routing Problems." In International Conference on Operations Research and Enterprise Systems. SCITEPRESS - Science and and Technology Publications, 2014. http://dx.doi.org/10.5220/0004833904340444.

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Lerouge, Mathieu, Céline Gicquel, Vincent Mousseau, and Wassila Ouerdane. "Counterfactual Explanations for Workforce Scheduling and Routing Problems." In 12th International Conference on Operations Research and Enterprise Systems. SCITEPRESS - Science and Technology Publications, 2023. http://dx.doi.org/10.5220/0011639900003396.

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Algethami, Haneen, and Dario Landa-Silva. "Diversity-based adaptive genetic algorithm for a Workforce Scheduling and Routing Problem." In 2017 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2017. http://dx.doi.org/10.1109/cec.2017.7969516.

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Laesanklang, Wasakorn, Dario Landa-Silva, and J. Arturo Castillo Salazar. "Mixed Integer Programming with Decomposition to Solve a Workforce Scheduling and Routing Problem." In International Conference on Operations Research and Enterprise Systems. SCITEPRESS - Science and and Technology Publications, 2015. http://dx.doi.org/10.5220/0005223602830293.

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Zhou, Yalan, Manhui Huang, Hong Wu, Guoming Chen, and Zhijian Wang. "Iterated Local Search with Hybrid Neighborhood Search for Workforce Scheduling and Routing Problem." In 2020 12th International Conference on Advanced Computational Intelligence (ICACI). IEEE, 2020. http://dx.doi.org/10.1109/icaci49185.2020.9177523.

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Algethami, Haneen, Dario Landa-Silva, and Anna Martínez-Gavara. "Selecting Genetic Operators to Maximise Preference Satisfaction in a Workforce Scheduling and Routing Problem." In 6th International Conference on Operations Research and Enterprise Systems. SCITEPRESS - Science and Technology Publications, 2017. http://dx.doi.org/10.5220/0006203304160423.

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Algethami, Haneen, Dario Landa-Silva, and Anna Martínez-Gavara. "Selecting Genetic Operators to Maximise Preference Satisfaction in a Workforce Scheduling and Routing Problem." In 6th International Conference on Operations Research and Enterprise Systems. SCITEPRESS - Science and Technology Publications, 2017. http://dx.doi.org/10.5220/0006203300001482.

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Morz, M., and N. Musliu. "Genetic algorithm for rotating workforce scheduling problem." In Second IEEE International Conference on Computational Cybernetics. IEEE, 2004. http://dx.doi.org/10.1109/icccyb.2004.1437685.

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He, Chengwan, and You Shi. "Workforce Scheduling and Routing for Home Health Care Services." In the 3rd International Conference. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3331453.3361673.

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