On the impact of real-time information on field service scheduling

Petrakis, Ioannis; Hass, Christian; Bichler, Martin

doi:10.1016/j.dss.2012.01.013

Cited by 22 publications

(16 citation statements)

References 35 publications

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“…An adaptive variable neighbourhood search improves solutions constructed by a randomised heuristic. Petrakis et al (2012) investigate different off-line and on-line mobile field force management solutions to schedule staff for maintenance and repair of mobile-phone base stations. Their results show that travel times are often lower in on-line solutions and that deadline penalties are considerably reduced.…”

Section: Literature Reviewmentioning

confidence: 99%

A discrete-event driven metaheuristic for dynamic home service routing with synchronised trip sharing

Fikar

Juan

Martinez

et al. 2016

EJIE

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It is common practice in the home service industry that each staff member operates a separate vehicle to visit customers. Facilitating trip sharing and walking policies allows reducing the number of required vehicles, however, often does not succeed due to operational difficulties in routing and planning. In particular, coordinating arrival times of staff members and vehicles at pickup locations introduces major complexity. Previous work in this field focusses on static problem settings where all data is known in advance. Real world-operations, however, are dynamic as cancellations or new requests can happen at any time. This requires decisions to be made in real-time. To assist planners, we propose a flexible discrete-event driven metaheuristic to deal with dynamic routing and scheduling scenarios using combined trip sharing and walking. The computational experiments show that our approach generates solutions in a fast and efficient way, thus, facilitating real-world operations and enabling rescheduling and rerouting. [(2016) 'A discrete-event driven metaheuristic for dynamic home service routing with synchronised trip sharing', European J.

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Section: Literature Reviewmentioning

confidence: 99%

A discrete-event driven metaheuristic for dynamic home service routing with synchronised trip sharing

Fikar

Juan

Martinez

et al. 2016

EJIE

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“…Most of the academic work is focused on route optimisation without assigning the right person to customers (Agnihothri, Sivasubramaniam, and Simmons 2002;Tang, Wilson, and Perevalov 2008;Petrakis, Hass, and Bichler 2012;Tricoire et al 2013). And the cooperation of engineers also hasn't received adequate attention in the problems modelling and algorithm designing.…”

Section: Introductionmentioning

confidence: 99%

“…Given this, this paper seeks to fill a gap in the literature by presenting a 0-1 programming model. The planning problem has similarities with different types of vehicle routing problem and vehicle routing problem with time windows, which were proved to be NP-hard by Petrakis, Hass, and Bichler (2012) and Solomon (1986). Therefore, the improved non-dominated sorting genetic algorithm-II (NSGA-II) is adopted to deal with this issue.…”

Section: Introductionmentioning

confidence: 99%

“…Scheduling flexibility is an important cofactor for exploiting the benefits of cross-training in labour scheduling environments (Easton 2011). Therefore, cross-trained workers scheduling is a key part of field service support with a service guarantee (Hill 1992;Tang, Wilson, and Perevalov 2008;Petrakis, Hass, and Bichler 2012). The primary challenge of workforce scheduling is to assign the right person to customers and plan an appropriate route for each worker with real-world constraints.…”

Section: Introductionmentioning

confidence: 99%

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Cross-trained workers scheduling for field service using improved NSGA-II

Zheng

et al. 2014

International Journal of Production Research

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The proper balancing of geographically distributed task schedules and the associated workforce distributions are critical determinants of productivity in any people-centric production environment. The paper has investigated the cross-trained workers scheduling problem considering the qualified personal allocation and temporally cooperation of engineers simultaneously. A 0-1 programming model is developed and the non-dominated sorting genetic algorithm-II (NSGA-II) is adopted to deal with the NP-hard problem. In order to enforce the NSGA-II, significant improvements are made to function the approach in a more efficient way. It is observed that the improved NSGA-II outperforms the original NSGA-II in the experimental test. The promising outcomes of the formulation in the experiment make its implementation easily customisable and transferable for solving other intricate problems in the context of skilled workforce scheduling. Furthermore, the modified NSGA II can be used as an efficient and effective tool for other multiobjective optimisation problems.

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“…This section briefly summarises some of the papers dealing with real-life examples of successful implementations of results from projects that have had a significant beneficial impact on the daily operations of a company and on their bottom-line. Papers on well-defined scheduling and rostering problems that assign tasks to the field workforce are not included here, since these do not take the travel times and routing constraints into account [18].…”

Section: Application Areasmentioning

confidence: 99%

A Decision Support System for Strategic, Tactical and Operational Visit Planning for on-the-Road Personnela DSS for Strategic, Tactical and Operational Visit Planning for on-the-Road Personnel

Rademeyer¹,

Lubinsky²

2017

SAJIE

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The use of a decision support system (DSS) for efficiently optimising and managing field workers' visits is discussed. This tool was designed after years of consulting experience and algorithmic research. It includes not only an innovative memetic algorithm to solve very large problems with realistic features and constraints, but also analytic tools and mapping capabilities to compare scenarios. As practitioners, we include some insights from case studies done at strategic, tactical, and operational decision levels. The system solves scenarios at all three decision levels simultaneously, not sequentially. The empirical studies highlight some misconceptions that are present in industry in planning visits for on-the-road personnel activities. OPSOMMINGDie gebruik van 'n besluitnemingsondersteuningstelsel om veldwerkers te bestuur en optimeer word beskou. Die stelsel is ontwikkel na jare se ondervinding as konsultante en navorsing oor algoritmes. Dit sluit nie net 'n innoverende memetiese algoritme in om baie groot probleme op te los nie, maar bevat ook analitiese funksies en 'n vermoë om scenario's met mekaar te vergelyk. As praktisyns sluit ons insigte in van gevallestudies wat ons gedoen het op strategiese, taktiese, en operasionele vlakke. Die stelsel los scenario's op al drie besluitnemingsvlakke gelyktydig, nie sekwensieel nie, op. Die empiriese studies lig 'n aantal wanopvattings uit wat in die praktyk oor die beplanning van reisende personeelaktiwiteite bestaan.

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On the impact of real-time information on field service scheduling

Cited by 22 publications

References 35 publications

A discrete-event driven metaheuristic for dynamic home service routing with synchronised trip sharing

A discrete-event driven metaheuristic for dynamic home service routing with synchronised trip sharing

Cross-trained workers scheduling for field service using improved NSGA-II

A Decision Support System for Strategic, Tactical and Operational Visit Planning for on-the-Road Personnela DSS for Strategic, Tactical and Operational Visit Planning for on-the-Road Personnel

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