The multi-shift vehicle routing problem with overtime

Ren, Yingtao; Dessouky, Maged; Ordóñez, Fernando

doi:10.1016/j.cor.2010.01.016

Cited by 29 publications

(11 citation statements)

References 28 publications

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“…• Constraints (2) and 3 • Constraints (6) are the sub-tour elimination constraints and ensure coherence of time variables. Parameter M is an upper bound of…”

Section: Problem Formulation 21 Classical Problemmentioning

confidence: 99%

Fuzzy Uncertainty Management in Multi-Shift Single-Vehicle Routing Problem

Nucci¹

2018

Adv. sci. technol. eng. syst. j.

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Our research deals with the single-vehicle routing problem (VRP) with multi-shift and fuzzy uncertainty. In such a problem, a company constantly uses one vehicle to serve demand over a scheduling period of different work shifts. Our issue relies on a routing problem in maintenance jobs, where a crew executes jobs in different sites. The crew runs during several work shifts but repeatedly returns to the depot before the shift ends. The goal is executing all the activities minimizing the makespan. We examine the impact of uncertainty in driving and maintenance processing time on system performance. We realize an Artificial Immune Heuristic to find optimal solutions considering both makespan and overtime avoidance. First, we introduce a framework to assess the uncertainty impact. Then, we produce a numerical company case study to examine the problem. Outcomes present significant improvements are obtained with the proposed approach.

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“…• Constraints (2) and 3 • Constraints (6) are the sub-tour elimination constraints and ensure coherence of time variables. Parameter M is an upper bound of…”

Section: Problem Formulation 21 Classical Problemmentioning

confidence: 99%

Fuzzy Uncertainty Management in Multi-Shift Single-Vehicle Routing Problem

Nucci¹

2018

Adv. sci. technol. eng. syst. j.

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“…The ma in goal is to reduce the costs of the letter-mail transportation. In [14], a vehicle routing problem including mu ltip le trips in a health care organization which operates about 240 buildings of medical offices in Southern California is treated. Finally, we mention Hernandez et al 2009[15] wh ich present a VRPMT applied in a context of optimizing the agronomic performance and its impact on the environment.…”

Section: The Vehicle Routing Problem Wi Th Multi Ple Tri Psmentioning

confidence: 99%

Profitable Vehicle Routing Problem with Multiple Trips: Modeling and Variable Neighborhood Descent Algorithm

Chbichib¹,

Mellouli²,

Chabchoub³

2013

AJOR

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In this paper, we tackle a new variant of the Veh icle Routing Problem (VRP) which comb ines two known variants namely the Profitable VRP and the VRP with Mult iple Trips. The resulting problem may be called the Profitable Vehicle Routing Problem with Multiple Trips. The main purpose is to cover and solve a more co mplex realistic situation of the distribution transportation. The profitability concept arises when only a subset of customers can be served due to the lack of means or for insufficiency of the offer. In this case, each customer is associated to an economical profit wh ich will be integrated to the objective function. The latter contains at hand the total collected profit minus the transportation costs. Each vehicle is allowed to perform several routes under a strict workday duration limit. This problem has a very practical interest especially for daily distribution schedules with limited vehicle fleets and short course transportation networks. We point out a new discursive approach for p rofits quantificat ion wh ich is mo re significant than those existing in the literature. We propose four equivalent mathematical formu lations for the problem which are tested and compared using CPLEX solver on small-size instances. Optimal solutions are identified. For large-size instance, two constructive heuristics are proposed and enhanced using Hill Climbing and Variable Neighborhood Descent algorithm based on a specific three-arrays-based coding structure. Finally, extensive co mputational experiments are performed including randomly generated instances and an extended and adapted benchmark fro m literature showing very satisfactory results.

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“…The Vehicular Routing Problem (VRP) is to deliver the goods from the central depot to the number of customers who had placed orders. The main objective is to find the routes and minimize the cost of distributing the goods [1]. Vehicle Routing Problem can be solved by two approaches, namely exact approach and heuristic approach.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Genetic Algorithm Optimization Models for Vehicular Routing Problems

Premkumar,

Baskaran,

Shanmugam

2019

IJEAT

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The Vehicle Routing Problem (VRP) is one of the most studied combinatorial optimization problems because of its practical relevance and complexity. Though there are several techniques have been proposed to solve the VRPs and its variants effectively, each technique has its own tradeoff values in terms of the performance factors. From this perspective, the work presented in this paper proposed an intelligent routing strategy for VRP based on distance values between the cities. The proposed strategy uses an enhanced model of Genetic Algorithm to find the optimal tour paths among the cities under distance based optimized tour path estimation scenarios. For distance-based optimization approach, experiments were performed on the standard benchmark TSP instances obtained from TSPLIB. A set of fine-grained result analyses demonstrated that the proposed model of routing strategies performed comparatively better w.r.t. the existing relevant approaches. By considering this problem as the base, a distinct model was developed as a set of assistive modules for Genetic Algorithms (GA), which are aimed at improving the overall efficiency of the typical GA, particularly for optimization problems. The capability of the proposed optimization models for VRP is demonstrated at various levels, particularly at the population initialization stage, using a set of well-defined experiments.

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The multi-shift vehicle routing problem with overtime

Cited by 29 publications

References 28 publications

Fuzzy Uncertainty Management in Multi-Shift Single-Vehicle Routing Problem

Fuzzy Uncertainty Management in Multi-Shift Single-Vehicle Routing Problem

Profitable Vehicle Routing Problem with Multiple Trips: Modeling and Variable Neighborhood Descent Algorithm

Enhanced Genetic Algorithm Optimization Models for Vehicular Routing Problems

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