A multilevel variable neighborhood search heuristic for a practical vehicle routing and driver scheduling problem

Abstract

The world's second largest producer of pork, Danish Crown, also provides a fresh meat supply logistics system within Denmark. This is used by the majority of supermarkets in Denmark. This article addresses an integrated vehicle routing and driver scheduling problem arising at Danish Crown in their fresh meat supply logistics system. The problem consists of a 1‐week planning horizon, heterogeneous vehicles, and drivers with predefined work regulations. These regulations include, among other things, predefined workdays, fixed starting time, maximum weekly working duration, and a break rule. The objective is to minimize the total delivery cost that is a weighted sum of two kinds of delivery costs. A multilevel variable neighborhood search heuristic is proposed for the problem. In a preprocessing step, the problem size is reduced through an aggregation procedure. Thereafter, the aggregated weekly planning problem is decomposed into daily planning problems, each of which is solved by a variable neighborhood search. Finally, the solution of the aggregated problem is expanded to that of the original problem. The method is implemented and tested on real‐life data consisting of up to 2,000 orders per week. Computational results show that the aggregation procedure and the decomposition strategy are very effective in solving this large scale problem, and our solutions are superior to the industrial solutions given the constraints considered in this work. © 2011 Wiley Periodicals, Inc. NETWORKS, Vol. 58(4), 311–322 2011

Real-time rescheduling and disruption management for public transit

“…Tabu search and a genetic algorithm are used separately to guide the solution approach. Zäpfel and Bögl (2008) and Wen et al (2011) investigated schedules for pickup-and-delivery using meta-heuristic approaches. Wen et al (2011) proposed a multilevel variable neighborhood search heuristic.…”

“…Zäpfel and Bögl (2008) and Wen et al (2011) investigated schedules for pickup-and-delivery using meta-heuristic approaches. Wen et al (2011) proposed a multilevel variable neighborhood search heuristic. When a maximum number of working hours of drivers apply daily rather than accumulatively across different days, the problem becomes many daily planning problems that could be solved independently.…”

Unified matheuristic for solving rich vehicle routing problems

“…The literature devoted to this challenging variant is scarce (Wen et al, 2011). Nevertheless, recent papers have been published e.g., (Haase et al, 2001, Freling et al, 2003, Xu et al, 2003, Goel, 2009, Zäpfel and Bögl, 2008, Wen et al, 2011. Note that the regulation of working hours can be modeled as additional constraints (see the section dedicated to driver regulations).…”

“…Driver regulations aim to provide safe driving, to reduce the number of accidents and to reduce the total costs. In recent years, there has been an increasing number of papers describing VRPs where a limited set of the European Union or United States regulations is taken into account (e.g., (Zäpfel and Bögl, 2008, Wen et al, 2011, Beaudry et al, 2010, Derigs et al, 2011b). Other studies include all parts of the mandatory legislation and the legal requirements, e.g., (Rancourt et al, 2013, Vidit, 2008 who studied the US regulation in his thesis.…”

“…Let us motivate our choice to select the VNS (Mladenovic and Hansen, 1997) to solve the RPTP. The VNS is an approach able to take into account a wide variety of constraints, which proves to be very efficient for solving complex VRPs (Wen et al, 2011, Schilde et al, 2011. This success may be explained either by its ability (i) to escape from local optima compared with population based metaheuristics; (ii) to exploit unexplored parts of the solution space by applying different problem specific neighborhoods.…”