Michel Gendreau - Academia.edu (original) (raw)
Papers by Michel Gendreau
European Journal of Operational Research, 2016
In this paper we consider the vehicle routing problem with hard time windows and stochastic servi... more In this paper we consider the vehicle routing problem with hard time windows and stochastic service times (VRPTW-ST); in this variant of the classic VRPTW the service times are random variables. In particular, given a set of vehicle routes, some of the actual service times might not lead to a feasible solution, given the customer time windows. We consider a chance-constrained program to model the VRPTW-ST and provide a new set partitioning formulation that includes a constraint on the minimum success probability of the set of vehicle routes. Under some mild conditions, we develop a method to exactly compute the success probability of the routes. We then solve the VRPTW-ST by a branch-price-and-cut algorithm, where the main challenges are in the solution of the subproblems of the column generation procedure. We adapt the dynamic programming algorithm to account for the probabilistic resource consumption by extending the label dimension and by providing new dominance rules. Extensive computational experiments prove the effectiveness of both the solution method and the stochastic model.
European Journal of Operational Research, 2015
We introduce the Integrative Cooperative Search (ICS), a multi-thread cooperative search method f... more We introduce the Integrative Cooperative Search (ICS), a multi-thread cooperative search method for multi-attribute combinatorial optimization problems. ICS musters the combined capabilities of a number of independent exact or meta-heuristic solution methods. A number of these methods work on sub-problems defined by suitably selected subsets of decision-set attributes of the problem, while others combine the resulting partial solutions into complete ones and, eventually, improve them. All these methods cooperate through an adaptive search-guidance mechanism, using the centralmemory cooperative search paradigm. Extensive numerical experiments explore the behavior of ICS and how the interest of the method through an application to the multidepot, periodic vehicle routing problem, for which ICS improves the results of the current state-of-the-art methods.
Meta-Heuristics, 1996
Abstract Roughly speaking, parallel local search techniques can be divided into three categories:... more Abstract Roughly speaking, parallel local search techniques can be divided into three categories: low-level parallelization strategies (eg, master-slave schemes), solutionspace partitioning methods and multi-thread procedures in which several processes explore ...
Networks, 2015
It is also the final version of the technical report named "A unifying view on timing problems an... more It is also the final version of the technical report named "A unifying view on timing problems and algorithms". This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
Computers & Operations Research, 2015
In this paper, we address the problem of determining the optimal fleet size for three vehicle rou... more In this paper, we address the problem of determining the optimal fleet size for three vehicle routing problems, i.e., multi-depot VRP, periodic VRP and multidepot periodic VRP. In each of these problems, we consider three kinds of constraints that are often found in reality, i.e., vehicle capacity, route duration and budget constraints. To tackle the problems, we propose a new Modular Heuristic Algorithm (MHA) whose exploration and exploitation strategies enable the algorithm to produce promising results. Extensive computational experiments show that MHA performs impressively well, in terms of solution quality and computational time, for the three problem classes.
2009 IEEE International Symposium on Parallel & Distributed Processing, 2009
... In CC Ribeiro and P. Hansen, editors, Essays and Surveys in Metaheuristics, Kluwer Academic P... more ... In CC Ribeiro and P. Hansen, editors, Essays and Surveys in Metaheuristics, Kluwer Academic Publishers, Norwell, MA, pages 263308. [13] PM Francis, KR Smilowitz and M. Tzur (2008). ... [19] A. Le Bouthillier and TG Crainic (2005). ...
Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference - GECCO '09, 2009
... Of course, enhancement of offspring through local search or more complex meta-heuristics, lea... more ... Of course, enhancement of offspring through local search or more complex meta-heuristics, leading to Lamar-ckian evolution, has proved its worth and is included from the beginning as appropriate for each specific application. ... [10] BL Golden, AA Assad and EW Wasil (2002). ...
Computers & Operations Research, 2015
In this paper, we consider tactical planning for a class of the multi-period vehicle routing prob... more In this paper, we consider tactical planning for a class of the multi-period vehicle routing problem (MPVRP). This problem involves optimizing daily product collections from several production locations over a given planning horizon. In this context, a single vehicle routing plan for the whole horizon must be prepared, and the seasonal variations in the producers' supplies must be taken into account. The production variations over the horizon are approximated using a sequence of periods, each corresponding to a production season, while the intra-period variations are neglected. We propose a mathematical model that is based on the two-stage a priori optimization paradigm. The first stage corresponds to the design of a plan which, in the second stage, takes the different periods into account. The proposed set-partitioning-based formulation is solved using a branch-and-price approach. The subproblem is a multi-period elementary shortest path problem with resource constraints (MPESPPRC), for which we propose an adaptation of the dynamic-programming-based label-correcting algorithm. Computational results show that this approach is able to solve instances with up to twenty producers and five periods.
European Journal of Operational Research, 2015
In this paper, we consider a deterministic multi-attribute vehicle routing problem derived from a... more In this paper, we consider a deterministic multi-attribute vehicle routing problem derived from a real-life milk collection system. This problem is characterized by the presence of a heterogeneous fleet of vehicles, multiple depots, and several resource constraints. A branch-and-price methodology is proposed to tackle the problem. In this methodology, different branching strategies, adapted to the special structure of the problem, are implemented and compared. The computational results show that the branch-and-price algorithm performs well in terms of solution quality and computational efficiency.
Journal of Heuristics, 2014
The contribution of infeasible solutions in heuristic searches for Vehicle Routing Problems (VRP)... more The contribution of infeasible solutions in heuristic searches for Vehicle Routing Problems (VRP) is not a subject of consensus in the metaheuristics community. Infeasible solutions may allow transitioning between structurally different feasible solutions, thus enhancing the search, but they also lead to more complex move evaluation procedures and wider search spaces. This paper introduces an experimental assessment of the impact of infeasible solutions on heuristic searches, through various empirical studies on local-improvement procedures, iterated local searches, and hybrid genetic algorithms for the VRP with time windows and other related variants with fleet mix, backhauls, and multiple periods. Four relaxation schemes are considered, allowing penalized late arrivals to customers, early and late arrivals, returns in time, or a flexible travel time relaxation. For all considered problems and methods, our experiments demonstrate the significant positive impact of penalized infeasible solution. Differences can also be observed between individual relaxation schemes. The "returns in time" and "flexible travel time" relaxations appear as the best options in terms of solution quality, CPU time, and scalability.
OR Spektrum, 1995
We study and compare synchronous parallelization strategies for tabu search. We identify the most... more We study and compare synchronous parallelization strategies for tabu search. We identify the most promising parallelization approaches, and evaluate the impact on performance and solution quality of some important algorithmic design parameters: length of the synchronization steps, number of processors, handling of exchanged information, etc. Parallelization approaches are implemented and compared by using a tabu search algorithm for multicommodity location-allocation problems with balancing requirements. Zusammenfassung. Die Arbeit befal3t sich mit synchronen Parallelisierungsstrategien ffir Tabu Search. Wir zeigen die vielversprechendsten Parallelisierungsans~itze auf und beurteilen deren Auswirkungen auf Leistungsverhalten und L6sungsgtite einiger wesentlicher Parameter; L~inge der Synchronisationsschritte, Anzahl der Prozessoren, Art der Kommunikationsbeziehungen etc. Die Paral-lelisierungsans~itze wurden implementiert und einander bei Anwendung eines Tabu Search-Verfahrens fur Mehrgtiter-Standort-Einzugsbereich-Probleme mit Ausgleichsbedingungen gegentibergestellt.
Operations Research, 2012
We propose an algorithmic framework that successfully addresses three vehicle routing problems: t... more We propose an algorithmic framework that successfully addresses three vehicle routing problems: the multidepot VRP, the periodic VRP, and the multidepot periodic VRP with capacitated vehicles and constrained route duration. The metaheuristic combines the exploration breadth of population-based evolutionary search, the aggressive-improvement capabilities of neighborhood-based metaheuristics, and advanced population-diversity management schemes. Extensive computational experiments show that the method performs impressively in terms of computational efficiency and solution quality, identifying either the best known solutions, including the optimal ones, or new best solutions for all currently available benchmark instances for the three problem classes. The proposed method also proves extremely competitive for the capacitated VRP.
Journal of the Operational Research Society, 2013
The dairy transportation problem consists of determining the best routes to be performed for coll... more The dairy transportation problem consists of determining the best routes to be performed for collecting milk from farms and delivering to processing plants. We study the particular case of the province of Quebec, where the Fédération des producteurs de lait du Québec (FPLQ) is responsible for negotiating the transportation cost on behalf of producers. Several issues are highlighted in the actual process of designing contracts such as using historical data. We propose an approach based on scenario analysis which consists of revising both the steps and the information used to construct the routes. We develop a generalized tabu search algorithm that integrates the different characteristics of the dairy transportation problem.
Journal of Heuristics, 2013
In this paper, we consider a variant of vehicle routing problems which is characterized by the pr... more In this paper, we consider a variant of vehicle routing problems which is characterized by the presence of a homogeneous fleet of vehicles, multiple depots, multiple periods and two kinds of constraints that are often found in reality, i.e., vehicle capacity and route duration constraints. The objective is to minimize total travel costs. Since the Vehicle Routing Problem has been proved to be NP-hard in the strong sense, an effective Path Relinking Algorithm (PRA) is designed for finding the best possible solutions to this problem. The proposed PRA incorporates several purposeful exploitation and exploration strategies that enable the algorithm to tackle the problem in two different settings: 1) As a stand-alone algorithm, and 2) As a part of a cooperative search algorithm called Integrative Cooperative Search (ICS). The performance of the proposed Path Relinking Algorithm is evaluated, in each of the above ways, based on various test problems. The computational results show that the developed PRA performs impressively, in both solution quality and computational efficiency.
INFORMS Journal on Computing, 1997
In this paper we present a classification of parallel tabu search metaheuristics based, on the on... more In this paper we present a classification of parallel tabu search metaheuristics based, on the one hand, on the control and communication strategies used in the design of the parallel tabu search procedures, and on the other hand, on how the search space is partitioned. These criteria are then used to review the parallel tabu search implementations described in the literature. The taxonomy is further illustrated by the results of several parallelization implementations of a tabu search procedure for multicommodity location-allocation problems with balancing requirements.
INFORMS Journal on Computing, 2009
This paper shows how local branching can be used to accelerate the classical Benders decompositio... more This paper shows how local branching can be used to accelerate the classical Benders decomposition algorithm. By applying local branching throughout the solution process, one can simultaneously improve both the lower and upper bounds. We also show how Benders feasibility cuts can be strengthened or replaced with local branching constraints. To assess the performance of the different algorithmic ideas presented in this hybrid solution approach, extensive computational experiments were performed on two families of network design problems. Numerical results clearly illustrate their benefits.
European Journal of Operational Research, 2014
Vehicle routing variants with multiple depots and mixed fleet present intricate combinatorial asp... more Vehicle routing variants with multiple depots and mixed fleet present intricate combinatorial aspects related to sequencing choices, vehicle type choices, depot choices, and depots positioning. This paper introduces a dynamic programming methodology for efficiently evaluating compound neighborhoods combining sequence-based moves with an optimal choice of vehicle and depot, and an optimal determination of the first customer to be visited in the route, called rotation. The assignment choices, making the richness of the problem, are thus no more addressed in the solution structure, but implicitly determined during each move evaluation. Two meta-heuristics relying on these concepts, an iterated local search and a hybrid genetic algorithm are presented. Extensive computational experiments demonstrate the remarkable performance of these methods on classic benchmark instances for multi-depot vehicle routing problems with and without fleet mix, as well as the notable contribution of the implicit depot choice and positioning methods to the search performance. The proposed concepts are fairly general, and widely applicable to many other vehicle routing variants.
European Journal of Operational Research, 2013
European Journal of Operational Research, 2014
Vehicle routing attributes are extra characteristics and decisions that complement the academic p... more Vehicle routing attributes are extra characteristics and decisions that complement the academic problem formulations and aim to properly account for real-life application needs. Hundreds of methods have been introduced in recent years for specific attributes, but the development of a single, general-purpose algorithm, which is both efficient and applicable to a wide family of variants remains a considerable challenge. Yet, such a development is critical for understanding the proper impact of attributes on resolution approaches, and to answer the needs of actual applications. This paper contributes towards addressing these challenges with a component-based design for heuristics, targeting multi-attribute vehicle routing problems, and an efficient generalpurpose solver. The proposed Unified Hybrid Genetic Search metaheuristic relies on problem-independent unified local search, genetic operators, and advanced diversity management methods. Problem specifics are confined to a limited part of the method and are addressed by means of assignment, sequencing, and route-evaluation components, which are automatically selected and adapted and provide the fundamental operators to manage attribute specificities. Extensive computational experiments on 29 prominent vehicle routing variants, 42 benchmark instance sets and overall 1099 instances, demonstrate the remarkable performance of the method which matches or outperforms the current state-of-the-art problem-tailored algorithms.
European Journal of Operational Research, 2016
In this paper we consider the vehicle routing problem with hard time windows and stochastic servi... more In this paper we consider the vehicle routing problem with hard time windows and stochastic service times (VRPTW-ST); in this variant of the classic VRPTW the service times are random variables. In particular, given a set of vehicle routes, some of the actual service times might not lead to a feasible solution, given the customer time windows. We consider a chance-constrained program to model the VRPTW-ST and provide a new set partitioning formulation that includes a constraint on the minimum success probability of the set of vehicle routes. Under some mild conditions, we develop a method to exactly compute the success probability of the routes. We then solve the VRPTW-ST by a branch-price-and-cut algorithm, where the main challenges are in the solution of the subproblems of the column generation procedure. We adapt the dynamic programming algorithm to account for the probabilistic resource consumption by extending the label dimension and by providing new dominance rules. Extensive computational experiments prove the effectiveness of both the solution method and the stochastic model.
European Journal of Operational Research, 2015
We introduce the Integrative Cooperative Search (ICS), a multi-thread cooperative search method f... more We introduce the Integrative Cooperative Search (ICS), a multi-thread cooperative search method for multi-attribute combinatorial optimization problems. ICS musters the combined capabilities of a number of independent exact or meta-heuristic solution methods. A number of these methods work on sub-problems defined by suitably selected subsets of decision-set attributes of the problem, while others combine the resulting partial solutions into complete ones and, eventually, improve them. All these methods cooperate through an adaptive search-guidance mechanism, using the centralmemory cooperative search paradigm. Extensive numerical experiments explore the behavior of ICS and how the interest of the method through an application to the multidepot, periodic vehicle routing problem, for which ICS improves the results of the current state-of-the-art methods.
Meta-Heuristics, 1996
Abstract Roughly speaking, parallel local search techniques can be divided into three categories:... more Abstract Roughly speaking, parallel local search techniques can be divided into three categories: low-level parallelization strategies (eg, master-slave schemes), solutionspace partitioning methods and multi-thread procedures in which several processes explore ...
Networks, 2015
It is also the final version of the technical report named "A unifying view on timing problems an... more It is also the final version of the technical report named "A unifying view on timing problems and algorithms". This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
Computers & Operations Research, 2015
In this paper, we address the problem of determining the optimal fleet size for three vehicle rou... more In this paper, we address the problem of determining the optimal fleet size for three vehicle routing problems, i.e., multi-depot VRP, periodic VRP and multidepot periodic VRP. In each of these problems, we consider three kinds of constraints that are often found in reality, i.e., vehicle capacity, route duration and budget constraints. To tackle the problems, we propose a new Modular Heuristic Algorithm (MHA) whose exploration and exploitation strategies enable the algorithm to produce promising results. Extensive computational experiments show that MHA performs impressively well, in terms of solution quality and computational time, for the three problem classes.
2009 IEEE International Symposium on Parallel & Distributed Processing, 2009
... In CC Ribeiro and P. Hansen, editors, Essays and Surveys in Metaheuristics, Kluwer Academic P... more ... In CC Ribeiro and P. Hansen, editors, Essays and Surveys in Metaheuristics, Kluwer Academic Publishers, Norwell, MA, pages 263308. [13] PM Francis, KR Smilowitz and M. Tzur (2008). ... [19] A. Le Bouthillier and TG Crainic (2005). ...
Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference - GECCO '09, 2009
... Of course, enhancement of offspring through local search or more complex meta-heuristics, lea... more ... Of course, enhancement of offspring through local search or more complex meta-heuristics, leading to Lamar-ckian evolution, has proved its worth and is included from the beginning as appropriate for each specific application. ... [10] BL Golden, AA Assad and EW Wasil (2002). ...
Computers & Operations Research, 2015
In this paper, we consider tactical planning for a class of the multi-period vehicle routing prob... more In this paper, we consider tactical planning for a class of the multi-period vehicle routing problem (MPVRP). This problem involves optimizing daily product collections from several production locations over a given planning horizon. In this context, a single vehicle routing plan for the whole horizon must be prepared, and the seasonal variations in the producers' supplies must be taken into account. The production variations over the horizon are approximated using a sequence of periods, each corresponding to a production season, while the intra-period variations are neglected. We propose a mathematical model that is based on the two-stage a priori optimization paradigm. The first stage corresponds to the design of a plan which, in the second stage, takes the different periods into account. The proposed set-partitioning-based formulation is solved using a branch-and-price approach. The subproblem is a multi-period elementary shortest path problem with resource constraints (MPESPPRC), for which we propose an adaptation of the dynamic-programming-based label-correcting algorithm. Computational results show that this approach is able to solve instances with up to twenty producers and five periods.
European Journal of Operational Research, 2015
In this paper, we consider a deterministic multi-attribute vehicle routing problem derived from a... more In this paper, we consider a deterministic multi-attribute vehicle routing problem derived from a real-life milk collection system. This problem is characterized by the presence of a heterogeneous fleet of vehicles, multiple depots, and several resource constraints. A branch-and-price methodology is proposed to tackle the problem. In this methodology, different branching strategies, adapted to the special structure of the problem, are implemented and compared. The computational results show that the branch-and-price algorithm performs well in terms of solution quality and computational efficiency.
Journal of Heuristics, 2014
The contribution of infeasible solutions in heuristic searches for Vehicle Routing Problems (VRP)... more The contribution of infeasible solutions in heuristic searches for Vehicle Routing Problems (VRP) is not a subject of consensus in the metaheuristics community. Infeasible solutions may allow transitioning between structurally different feasible solutions, thus enhancing the search, but they also lead to more complex move evaluation procedures and wider search spaces. This paper introduces an experimental assessment of the impact of infeasible solutions on heuristic searches, through various empirical studies on local-improvement procedures, iterated local searches, and hybrid genetic algorithms for the VRP with time windows and other related variants with fleet mix, backhauls, and multiple periods. Four relaxation schemes are considered, allowing penalized late arrivals to customers, early and late arrivals, returns in time, or a flexible travel time relaxation. For all considered problems and methods, our experiments demonstrate the significant positive impact of penalized infeasible solution. Differences can also be observed between individual relaxation schemes. The "returns in time" and "flexible travel time" relaxations appear as the best options in terms of solution quality, CPU time, and scalability.
OR Spektrum, 1995
We study and compare synchronous parallelization strategies for tabu search. We identify the most... more We study and compare synchronous parallelization strategies for tabu search. We identify the most promising parallelization approaches, and evaluate the impact on performance and solution quality of some important algorithmic design parameters: length of the synchronization steps, number of processors, handling of exchanged information, etc. Parallelization approaches are implemented and compared by using a tabu search algorithm for multicommodity location-allocation problems with balancing requirements. Zusammenfassung. Die Arbeit befal3t sich mit synchronen Parallelisierungsstrategien ffir Tabu Search. Wir zeigen die vielversprechendsten Parallelisierungsans~itze auf und beurteilen deren Auswirkungen auf Leistungsverhalten und L6sungsgtite einiger wesentlicher Parameter; L~inge der Synchronisationsschritte, Anzahl der Prozessoren, Art der Kommunikationsbeziehungen etc. Die Paral-lelisierungsans~itze wurden implementiert und einander bei Anwendung eines Tabu Search-Verfahrens fur Mehrgtiter-Standort-Einzugsbereich-Probleme mit Ausgleichsbedingungen gegentibergestellt.
Operations Research, 2012
We propose an algorithmic framework that successfully addresses three vehicle routing problems: t... more We propose an algorithmic framework that successfully addresses three vehicle routing problems: the multidepot VRP, the periodic VRP, and the multidepot periodic VRP with capacitated vehicles and constrained route duration. The metaheuristic combines the exploration breadth of population-based evolutionary search, the aggressive-improvement capabilities of neighborhood-based metaheuristics, and advanced population-diversity management schemes. Extensive computational experiments show that the method performs impressively in terms of computational efficiency and solution quality, identifying either the best known solutions, including the optimal ones, or new best solutions for all currently available benchmark instances for the three problem classes. The proposed method also proves extremely competitive for the capacitated VRP.
Journal of the Operational Research Society, 2013
The dairy transportation problem consists of determining the best routes to be performed for coll... more The dairy transportation problem consists of determining the best routes to be performed for collecting milk from farms and delivering to processing plants. We study the particular case of the province of Quebec, where the Fédération des producteurs de lait du Québec (FPLQ) is responsible for negotiating the transportation cost on behalf of producers. Several issues are highlighted in the actual process of designing contracts such as using historical data. We propose an approach based on scenario analysis which consists of revising both the steps and the information used to construct the routes. We develop a generalized tabu search algorithm that integrates the different characteristics of the dairy transportation problem.
Journal of Heuristics, 2013
In this paper, we consider a variant of vehicle routing problems which is characterized by the pr... more In this paper, we consider a variant of vehicle routing problems which is characterized by the presence of a homogeneous fleet of vehicles, multiple depots, multiple periods and two kinds of constraints that are often found in reality, i.e., vehicle capacity and route duration constraints. The objective is to minimize total travel costs. Since the Vehicle Routing Problem has been proved to be NP-hard in the strong sense, an effective Path Relinking Algorithm (PRA) is designed for finding the best possible solutions to this problem. The proposed PRA incorporates several purposeful exploitation and exploration strategies that enable the algorithm to tackle the problem in two different settings: 1) As a stand-alone algorithm, and 2) As a part of a cooperative search algorithm called Integrative Cooperative Search (ICS). The performance of the proposed Path Relinking Algorithm is evaluated, in each of the above ways, based on various test problems. The computational results show that the developed PRA performs impressively, in both solution quality and computational efficiency.
INFORMS Journal on Computing, 1997
In this paper we present a classification of parallel tabu search metaheuristics based, on the on... more In this paper we present a classification of parallel tabu search metaheuristics based, on the one hand, on the control and communication strategies used in the design of the parallel tabu search procedures, and on the other hand, on how the search space is partitioned. These criteria are then used to review the parallel tabu search implementations described in the literature. The taxonomy is further illustrated by the results of several parallelization implementations of a tabu search procedure for multicommodity location-allocation problems with balancing requirements.
INFORMS Journal on Computing, 2009
This paper shows how local branching can be used to accelerate the classical Benders decompositio... more This paper shows how local branching can be used to accelerate the classical Benders decomposition algorithm. By applying local branching throughout the solution process, one can simultaneously improve both the lower and upper bounds. We also show how Benders feasibility cuts can be strengthened or replaced with local branching constraints. To assess the performance of the different algorithmic ideas presented in this hybrid solution approach, extensive computational experiments were performed on two families of network design problems. Numerical results clearly illustrate their benefits.
European Journal of Operational Research, 2014
Vehicle routing variants with multiple depots and mixed fleet present intricate combinatorial asp... more Vehicle routing variants with multiple depots and mixed fleet present intricate combinatorial aspects related to sequencing choices, vehicle type choices, depot choices, and depots positioning. This paper introduces a dynamic programming methodology for efficiently evaluating compound neighborhoods combining sequence-based moves with an optimal choice of vehicle and depot, and an optimal determination of the first customer to be visited in the route, called rotation. The assignment choices, making the richness of the problem, are thus no more addressed in the solution structure, but implicitly determined during each move evaluation. Two meta-heuristics relying on these concepts, an iterated local search and a hybrid genetic algorithm are presented. Extensive computational experiments demonstrate the remarkable performance of these methods on classic benchmark instances for multi-depot vehicle routing problems with and without fleet mix, as well as the notable contribution of the implicit depot choice and positioning methods to the search performance. The proposed concepts are fairly general, and widely applicable to many other vehicle routing variants.
European Journal of Operational Research, 2013
European Journal of Operational Research, 2014
Vehicle routing attributes are extra characteristics and decisions that complement the academic p... more Vehicle routing attributes are extra characteristics and decisions that complement the academic problem formulations and aim to properly account for real-life application needs. Hundreds of methods have been introduced in recent years for specific attributes, but the development of a single, general-purpose algorithm, which is both efficient and applicable to a wide family of variants remains a considerable challenge. Yet, such a development is critical for understanding the proper impact of attributes on resolution approaches, and to answer the needs of actual applications. This paper contributes towards addressing these challenges with a component-based design for heuristics, targeting multi-attribute vehicle routing problems, and an efficient generalpurpose solver. The proposed Unified Hybrid Genetic Search metaheuristic relies on problem-independent unified local search, genetic operators, and advanced diversity management methods. Problem specifics are confined to a limited part of the method and are addressed by means of assignment, sequencing, and route-evaluation components, which are automatically selected and adapted and provide the fundamental operators to manage attribute specificities. Extensive computational experiments on 29 prominent vehicle routing variants, 42 benchmark instance sets and overall 1099 instances, demonstrate the remarkable performance of the method which matches or outperforms the current state-of-the-art problem-tailored algorithms.