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Resource constrained routing and scheduling: Review and research prospects
In the service industry, it is crucial to efficiently allocate scarce resources to perform tasks and meet particular service requirements. What considerably complicates matters is when these resources, for example skilled technicians, nurses, and home carers have to visit different customer locations. This paper provides a comprehensive survey on resource constrained routing and scheduling that unveils the problem characteristics with respect to resource qualifications, service requirements and problem objectives. It also identifies the most effective exact and heuristic algorithms for this class of problems. The paper closes with several research prospects
Service scheduling and vehicle routing problem to minimise the risk of missing appointments
This research studies a workforce scheduling and vehicle routing problem where technicians drive a vehicle to customer locations to perform service tasks. The service times and travel times are subject to stochastic events. There is an agreed time window for starting each service task. The risk of missing the time window for a task is defined as the probability that the technician assigned to the task arrives at the customer site later than the time window. The problem is to generate a schedule that minimises the maximum of risks and the sum of risks of all the tasks considering the effect of skill levels and task priorities. A new approach is taken to build schedules that minimise the risks of missing appointments as well as the risks of technicians not being able to complete their daily tours on time.We first analyse the probability distribution of the arrival time to any customer location considering the distributions of activities prior to this arrival. Based on the analysis, an efficient estimation method for calculating the risks is proposed, which is highly accurate and this is verified by comparing the results of the estimation method with a numerical integral method.We then develop three new workforce scheduling and vehicle routing models that minimise the risks with different considerations such as an identical standard deviation of the duration for all uncertain tasks in the linear risk minimisation model, and task priorities in the priority task risk minimisation model. A simulated annealing algorithm is implemented for solving the models at the start of the day and for re-optimisation during the day. Computational experiments are carried out to compare the results of the risk minimisation models with those of the traditional travel cost model. The performance is measured using risks and robustness. Simulation is used to compare the numbers of missed appointments and test the effect of re-optimisation.The results of the experiments demonstrate that the new models significantly reduce the risks and generate schedules with more contingency time allowances. Simulation results also show that re-optimisation reduces the number of missed appointments significantly. The risk calculation methods and risk minimisation algorithm are applied to a real-world problem in the telecommunication sector.</div
Scheduling and Routing Milk from Farm to Processors by a Cooperative
A milk marketing cooperative (MMC) was created by Florida dairy farmers to link the primary supply of fluid milk with the derived demand of processors in the vertical market. For any given milk supply, the revenue or return to farmers per unit of milk is the average milk price received by the MMC minus the MMC’s transfer cost. An important task for the MMC is to operate the fluid milk hauling system that optimizes the MMC’s milk transfer cost (routing and scheduling cost) subject to farm and plant schedules. The objective of this study is to determine if it is economically feasible to implement a more efficient routing and scheduling of farm-to-plant milk collection by the MMC.cooperatives, margins, milk, routing, scheduling, Demand and Price Analysis, Productivity Analysis,
Enhanced Iterated local search for the technician routing and scheduling problem
Most public facilities in the European countries, including France, Germany,
and the UK, were built during the reconstruction projects between 1950 and
1980. Owing to the deteriorating state of such vital infrastructure has become
relatively expensive in the recent decades. A significant part of the
maintenance operation costs is spent on the technical staff. Therefore, the
optimal use of the available workforce is essential to optimize the operation
costs. This includes planning technical interventions, workload balancing,
productivity improvement, etc. In this paper, we focus on the routing of
technicians and scheduling of their tasks. We address for this purpose a
variant of the workforce scheduling problem called the technician routing and
scheduling problem (TRSP). This problem has applications in different fields,
such as transportation infrastructure (rail and road networks),
telecommunications, and sewage facilities. To solve the TRSP, we propose an
enhanced iterated local search (eILS) approach. The enhancement of the ILS
firstly includes an intensification procedure that incorporates a set of local
search operators and removal-repair heuristics crafted for the TRSP. Next, four
different mechanisms are used in the perturbation phase. Finally, an elite set
of solutions is used to extensively explore the neighborhood of local optima as
well as to enhance diversification during search space exploration. To measure
the performance of the proposed method, experiments were conducted based on
benchmark instances from the literature, and the results obtained were compared
with those of an existing method. Our method achieved very good results, since
it reached the best overall gap, which is three times lower than that of the
literature. Furthermore, eILS improved the best-known solution for
instances among a total of while maintaining reasonable computational
times.Comment: Submitted manuscript to Computers and Operations Research journal. 34
pages, 7 figures, 6 table
On the Technician Routing and Scheduling Problem
ISBN 978-88-900984-3-7International audienceThe technician routing and scheduling problem consists in routing and scheduling a crew of technicians in order to attend a set of service requests, subject to skill, tool, and spare part constraints. In this study we propose a formal definition of the problem and present a constructive heuristic and a large neighborhood search optimization algorithm
Coordinating technician allocation and maintenance routing for offshore wind farms
A maintenance activity at offshore wind farms requires a combination of technicians with different skills. At an operational level, it is important to fully utilize and coordinate technicians in order to increase efficiency of the short-term maintenance planning. In this paper, we investigate sharing of technicians between wind farms over multiple periods, while determining per period vessel routes for delivering and picking up technicians. The problem can be considered as a novel variant of the multi-period multi-commodity pick up and delivery problem. We develop an adaptive large neighborhood search heuristic which achieves high-quality, and often optimal, solutions on benchmark instances from the literature. The heuristic is used to explore the benefits of different sharing policies. By sharing technicians, both the flexibility of the daily planning is improved and the expected maintenance costs are reduced. In addition, the increased flexibility results in fewer vessel trips and increases the decision maker’s ability to cope with extreme scenarios encountered in the short-term maintenance planning
Incorporating risk in field services operational planning process
© Springer Nature Switzerland AG 2018. This paper presents a model for the risk minimisation objective in the Stochastic Vehicle Routing Problem (SVRP). In the studied variant of SVRP, service times and travel times are subject to stochastic events, and a time window is constraining the start time for service task. Required skill levels and task priorities increase the complexity of this problem. Most previous research uses a chance-constrained approach to the problem and their objectives are related to traditional routing costs whilst a different approach was taken in this paper. The risk of missing a task is defined as the probability that the technician assigned to the task arrives at the customer site later than the time window. The problem studied in this paper is to generate a schedule that minimises the maximum of risks and sum of risks over all the tasks considering the effect of skill levels and task priorities. The stochastic duration of each task is supposed to follow a known normal distribution. However, the distribution of the start time of the service at a customer site will not be normally distributed due to time window constraints. A method is proposed and tested to approximate the start time distribution as normal. Moreover, a linear model can be obtained assuming identical variance of task durations. Additionally Simulated Annealing method was applied to solve the problem. Results of this work have been applied to an industrial case of SVRP where field engineering individuals drive to customer sites to provide time-constrained services. This original approach gives a robust schedule and allows organisations to pay more attention to increasing customer satisfaction and become more competitive in the market
Workload Equity in Vehicle Routing Problems: A Survey and Analysis
Over the past two decades, equity aspects have been considered in a growing
number of models and methods for vehicle routing problems (VRPs). Equity
concerns most often relate to fairly allocating workloads and to balancing the
utilization of resources, and many practical applications have been reported in
the literature. However, there has been only limited discussion about how
workload equity should be modeled in VRPs, and various measures for optimizing
such objectives have been proposed and implemented without a critical
evaluation of their respective merits and consequences.
This article addresses this gap with an analysis of classical and alternative
equity functions for biobjective VRP models. In our survey, we review and
categorize the existing literature on equitable VRPs. In the analysis, we
identify a set of axiomatic properties that an ideal equity measure should
satisfy, collect six common measures, and point out important connections
between their properties and those of the resulting Pareto-optimal solutions.
To gauge the extent of these implications, we also conduct a numerical study on
small biobjective VRP instances solvable to optimality. Our study reveals two
undesirable consequences when optimizing equity with nonmonotonic functions:
Pareto-optimal solutions can consist of non-TSP-optimal tours, and even if all
tours are TSP optimal, Pareto-optimal solutions can be workload inconsistent,
i.e. composed of tours whose workloads are all equal to or longer than those of
other Pareto-optimal solutions. We show that the extent of these phenomena
should not be underestimated. The results of our biobjective analysis are valid
also for weighted sum, constraint-based, or single-objective models. Based on
this analysis, we conclude that monotonic equity functions are more appropriate
for certain types of VRP models, and suggest promising avenues for further
research.Comment: Accepted Manuscrip
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