Optimization of Maintenance Planning and Routing Problems

Dahite, Lamiaa; Kadrani, Abdeslam; Benmansour, Rachid; Guibadj, Rym Nesrine; Fonlupt, Cyril

doi:10.1007/978-3-030-44932-2_7

Cited by 2 publications

(6 citation statements)

References 9 publications

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“…It is equal to the start time of task three associated with the same machine, and that precedes task four. The data of this specified instance is detailed in [18].…”

Section: Solution Representation and Constraints Handlingmentioning

confidence: 99%

“…We use approximately the same order as the literature for VRP problems [19,20]. The results of our previous work [18] show that with well-chosen operators, the GVNS algorithm is an effective method to solve the single objective version of our problem. Its general structure can be applied to improve other methods performance [21].…”

Section: Local Search Procedures and Neighborhood Structuresmentioning

confidence: 99%

“…Each point in P generated with the MOBI/P procedure that is not in the archive A is evaluated to enter this latter or not (steps [13][14][15][16][17][18][19]. The solution x is included in the archive A if it is non-dominated by s and replaces the current solution s. This replacement of the current solution s by a solution that dominates it or that is incomparable to it is another new feature used.…”

Section: Updating Non-dominated Solutions Setmentioning

confidence: 99%

“…The depot time window is the interval between the lower bound a 0 = 0 and the upper bound b n+1 . For this class of instances, b n+1 = H. These data are shown in [18]. There are six machines that may need more than one maintenance task in the planning horizon in the class of instances Re.…”

Section: Instances Descriptionmentioning

confidence: 99%

“…The pseudo-code of mono-objective GVNS and VND are shown in [18]. The monoobjective GVNS can directly be obtained with MOGVNS/D when the initial population is reduced to one individual.…”

Section: Parameter Setting and Performance Metricsmentioning

confidence: 99%

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Multi-Objective Model and Variable Neighborhood Search Algorithms for the Joint Maintenance Scheduling and Workforce Routing Problem

et al. 2022

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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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“…It is equal to the start time of task three associated with the same machine, and that precedes task four. The data of this specified instance is detailed in [18].…”

Section: Solution Representation and Constraints Handlingmentioning

confidence: 99%

Section: Local Search Procedures and Neighborhood Structuresmentioning

confidence: 99%

Section: Updating Non-dominated Solutions Setmentioning

confidence: 99%

Section: Instances Descriptionmentioning

confidence: 99%

“…The pseudo-code of mono-objective GVNS and VND are shown in [18]. The monoobjective GVNS can directly be obtained with MOGVNS/D when the initial population is reduced to one individual.…”

Section: Parameter Setting and Performance Metricsmentioning

confidence: 99%

See 3 more Smart Citations