Victor Pillac | NICTA - Academia.edu (original) (raw)

Papers by Victor Pillac

The real-time operation of a fleet of vehicles introduces challenging optimization problems resea... more The real-time operation of a fleet of vehicles introduces challenging optimization problems researches in a wide range of applications, thus, it is appealing to both academia and practitioners in industry. In this work we focus on dynamic vehicle routing problems and present an event-driven framework that can anticipate unknown changes in the problem information. The proposed framework is intrinsically parallelized to take advantage of modern multi-core and multi-threaded computing architectures. It is also designed to be easily embeddable in decision support systems that cope with a wide range of contexts and side constraints. We illustrate the flexibility of the framework by showing how it can be adapted to tackle the dynamic vehicle routing problem with stochastic demands. Computational results show that while our approach is competitive against state-of-the art algorithms, it still ensures greater reactivity and requires less assumptions (e.g., demand distributions).

Evacuation planning is a critical aspect of disaster preparedness and response to minimize the nu... more Evacuation planning is a critical aspect of disaster preparedness and response to minimize the number of people exposed to a threat. Controlled evacuations aim at managing the flow of evacuees as efficiently as possible and have been shown to produce significant benefits compared to self-evacuations. However, existing approaches do not capture the delays introduced by diverging and crossing evacuation routes, although evidence from actual evacuations highlights that these can
lead to significant congestion. This paper introduces the concept of convergent evacuation plans to tackle this issue. It presents a MIP model to obtain optimal convergent evacuation plans which, unfortunately, does not scale to realistic instances. The paper then proposes a two-stage approach that separates the route design and the evacuation scheduling. Experimental results on a real case study show that the two-stage approach produces better primal bounds than the MIP model and is two orders of magnitude faster; It also produces dual bounds stronger than the linear relaxation of the MIP model. Finally, simulations of the evacuation demonstrate that convergent evacuation plans outperform existing approaches for realistic driver behaviors.

Evacuation planning and scheduling is a critical aspect of disaster management and national secur... more Evacuation planning and scheduling is a critical aspect of disaster management and national security applications. This paper proposes a conflict-based path-generation approach for evacuation planning. Its key idea is to generate evacuation routes lazily for evacuated areas and to optimize the evacuation over these routes in a master problem. Each new path is generated to remedy conflicts in the evacuation and adds new columns and a new row in the master problem. The algorithm is applied to massive flood scenarios in the Hawkesbury-Nepean river (West Sydney, Australia) which require evacuating in the order of 70,000 persons. The proposed approach reduces the number of variables from 4,500,000 in a Mixed Integer Programming (MIP) formulation to 30,000 in the case study. With this approach, realistic evacuations scenarios can be solved near-optimally in real time, supporting both evacuation planning in strategic, tactical, and operational environments.

Within the wide scope of logistics management, transportation plays a central role and is a cruci... more Within the wide scope of logistics management, transportation plays a central role and is a crucial activity in both production and service industry. Among others, it allows for the timely distribution of goods and services between suppliers, production units, warehouses, retailers, and final customers.

Abstract A number of technological advances have led to a renewed interest on dynamic vehicle rou... more Abstract A number of technological advances have led to a renewed interest on dynamic vehicle routing problems. This survey classifies routing problems from the perspective of information quality and evolution. After presenting a general description of dynamic routing, we introduce the notion of degree of dynamism, and present a comprehensive review of applications and solution methods for dynamic vehicle routing problems.

Decision Support Systems, 2012

The real-time operation of a fleet of vehicles introduces challenging optimization problems. In t... more The real-time operation of a fleet of vehicles introduces challenging optimization problems. In this work, we propose an event-driven framework that anticipates unknown changes arising in the context of dynamic vehicle routing. The framework is intrinsically parallelized to take advantage of modern multi-core and multi-threaded computing architectures. It is also designed to be easily embeddable in decision support systems that cope with a wide range of contexts and side constraints. We illustrate the flexibility of the framework by showing how it can be adapted to tackle the dynamic vehicle routing problem with stochastic demands.

The Technician Routing and Scheduling Problem (TRSP) consists in routing staff to serve requests ... more The Technician Routing and Scheduling Problem (TRSP) consists in routing staff to serve requests for service, taking into account time windows, skills, tools, and spare parts. Typical applications include maintenance operations and staff routing in telecoms, public utilities, and in the health care industry. In this paper, we present a formal definition of the TRSP, discuss its relation with the Vehicle Routing Problem with Time Windows (VRPTW), and review related research. From a methodological perspective, we describe a matheuristic composed of a constructive heuristic, a parallel Adaptive Large Neighborhood Search, and a mathematical programming based post-optimization procedure that successfully tackles the TRSP. We validate the matheuristic on the Solomon VRPTW instances, where we achieve an average gap of 0.23% , and matched 44 out of 55 optimal solutions. Finally, we illustrate how the matheuristic successfully solves a set of TRSP instances extended from the Solomon benchmark.

Technical reports by Victor Pillac

The Technician Routing and Scheduling Problem (TRSP) consists in routing staff to serve requests ... more The Technician Routing and Scheduling Problem (TRSP) consists in routing staff to serve requests for service, taking into account time windows, skills, tools, and spare parts. Typical applications include maintenance operations and staff routing in telecoms, public utilities, and in the health care industry. In this paper we tackle the Dynamic TRSP (D-TRSP) in which new requests appear over time. We propose a fast reoptimization approach based on a parallel Adaptive Large Neighborhood Search (pALNS) and a Multiple Plan Approach (MPA). Finally, we present computational experiments on randomly generated instances.

The present work deals with dynamic vehicle routing problems in which new customers appear during... more The present work deals with dynamic vehicle routing problems in which new customers appear during the design or execution of the routing. We propose a parallel Adaptive Large Neighborhood Search (pALNS) that produces high quality routes in a limited computational time. Then, we introduce the notion of driver inconvenience and dene a bi-objective optimization problem that minimizes the cost of routing while maintaining its consistency throughout the day.

Talks by Victor Pillac

The Technician Routing and Scheduling Problem (TRSP) deals with a limited crew of technicians K t... more The Technician Routing and Scheduling Problem (TRSP) deals with a limited crew of technicians K that serves a set of requests R. In the TRSP, each technician has a set of skills, tools, and spare parts, while requests require a subset of each. The problem is then to design a set of tours of minimal total duration such that each request is visited exactly once, within its time window, by a technician with the required skills, tools, and spare parts.

9th Metaheuristics International Conference (MIC 2011), Udine, Italy, 2011

The technician routing and scheduling problem consists in routing and scheduling a crew of techni... more The technician routing and scheduling problem consists in routing and scheduling a crew of technicians in order to attend a set of service requests, subject to skill, tool, and spare part constraints. In this study we propose a formal definition of the problem and present a constructive heuristic and a large neighborhood search optimization algorithm.

ROADEF 2012, Apr 11, 2012

Vehicle Routing Problems (VRPs) consider the operation of a fleet of vehicles that need to servic... more Vehicle Routing Problems (VRPs) consider the operation of a fleet of vehicles that need to service customer requests. The underlying problem consists in designing a set of routes that visit all customers, optimizing one or multiple objectives. Dynamic Vehicle Routing Problems (D-VRPs) are an extension of classical VRPs in which the information available to the decision maker changes or is updated dynamically.

ROADEF 2011

The Vehicle Routing Problem with Stochastic Demands (VRPSD) is a variation of the classical Capac... more The Vehicle Routing Problem with Stochastic Demands (VRPSD) is a variation of the classical Capacitated Vehicle Routing Problem (CVRP). In contrast to the deterministic CVRP, in the VRPSD the demand of each customer is modeled as a random variable and its realization is only known upon vehicle arrival to the customer site. Under this uncertain scenario, a possible outcome is that the demand of a customer ends up exceeding the remaining capacity of the vehicle, leading to a route failure. In this study we will focus on the single vehicle VRPSD in which the fleet is limited to one vehicle with finite capacity, that can execute various routes sequentially. The present work is based on an adaptation of an optimization framework developed initially for the vehicle routing problem with dynamic customers (i.e., customers appear while the vehicles are executing their routes).

ALIO-INFORMS 2010, Jun 2010

Traditional approaches for the VRPSD aim at designing a-priori robust plans that avoid potential ... more Traditional approaches for the VRPSD aim at designing a-priori robust plans that avoid potential route failures. However, the widespread and inexpensive real-time communication and geolocalization technologies have opened promising perspectives in this field. We illustrate on the VRPSD the flexibility of jMSA, a generic framework for Multiple Scenario Approach. Preliminary results show that a continuous re-optimization leads to reductions in route failures and improvements in cost efficiency.

The real-time operation of a fleet of vehicles introduces challenging optimization problems resea... more The real-time operation of a fleet of vehicles introduces challenging optimization problems researches in a wide range of applications, thus, it is appealing to both academia and practitioners in industry. In this work we focus on dynamic vehicle routing problems and present an event-driven framework that can anticipate unknown changes in the problem information. The proposed framework is intrinsically parallelized to take advantage of modern multi-core and multi-threaded computing architectures. It is also designed to be easily embeddable in decision support systems that cope with a wide range of contexts and side constraints. We illustrate the flexibility of the framework by showing how it can be adapted to tackle the dynamic vehicle routing problem with stochastic demands. Computational results show that while our approach is competitive against state-of-the art algorithms, it still ensures greater reactivity and requires less assumptions (e.g., demand distributions).

Evacuation planning is a critical aspect of disaster preparedness and response to minimize the nu... more Evacuation planning is a critical aspect of disaster preparedness and response to minimize the number of people exposed to a threat. Controlled evacuations aim at managing the flow of evacuees as efficiently as possible and have been shown to produce significant benefits compared to self-evacuations. However, existing approaches do not capture the delays introduced by diverging and crossing evacuation routes, although evidence from actual evacuations highlights that these can
lead to significant congestion. This paper introduces the concept of convergent evacuation plans to tackle this issue. It presents a MIP model to obtain optimal convergent evacuation plans which, unfortunately, does not scale to realistic instances. The paper then proposes a two-stage approach that separates the route design and the evacuation scheduling. Experimental results on a real case study show that the two-stage approach produces better primal bounds than the MIP model and is two orders of magnitude faster; It also produces dual bounds stronger than the linear relaxation of the MIP model. Finally, simulations of the evacuation demonstrate that convergent evacuation plans outperform existing approaches for realistic driver behaviors.

Evacuation planning and scheduling is a critical aspect of disaster management and national secur... more Evacuation planning and scheduling is a critical aspect of disaster management and national security applications. This paper proposes a conflict-based path-generation approach for evacuation planning. Its key idea is to generate evacuation routes lazily for evacuated areas and to optimize the evacuation over these routes in a master problem. Each new path is generated to remedy conflicts in the evacuation and adds new columns and a new row in the master problem. The algorithm is applied to massive flood scenarios in the Hawkesbury-Nepean river (West Sydney, Australia) which require evacuating in the order of 70,000 persons. The proposed approach reduces the number of variables from 4,500,000 in a Mixed Integer Programming (MIP) formulation to 30,000 in the case study. With this approach, realistic evacuations scenarios can be solved near-optimally in real time, supporting both evacuation planning in strategic, tactical, and operational environments.

Within the wide scope of logistics management, transportation plays a central role and is a cruci... more Within the wide scope of logistics management, transportation plays a central role and is a crucial activity in both production and service industry. Among others, it allows for the timely distribution of goods and services between suppliers, production units, warehouses, retailers, and final customers.

Abstract A number of technological advances have led to a renewed interest on dynamic vehicle rou... more Abstract A number of technological advances have led to a renewed interest on dynamic vehicle routing problems. This survey classifies routing problems from the perspective of information quality and evolution. After presenting a general description of dynamic routing, we introduce the notion of degree of dynamism, and present a comprehensive review of applications and solution methods for dynamic vehicle routing problems.

Decision Support Systems, 2012

The real-time operation of a fleet of vehicles introduces challenging optimization problems. In t... more The real-time operation of a fleet of vehicles introduces challenging optimization problems. In this work, we propose an event-driven framework that anticipates unknown changes arising in the context of dynamic vehicle routing. The framework is intrinsically parallelized to take advantage of modern multi-core and multi-threaded computing architectures. It is also designed to be easily embeddable in decision support systems that cope with a wide range of contexts and side constraints. We illustrate the flexibility of the framework by showing how it can be adapted to tackle the dynamic vehicle routing problem with stochastic demands.

The Technician Routing and Scheduling Problem (TRSP) consists in routing staff to serve requests ... more The Technician Routing and Scheduling Problem (TRSP) consists in routing staff to serve requests for service, taking into account time windows, skills, tools, and spare parts. Typical applications include maintenance operations and staff routing in telecoms, public utilities, and in the health care industry. In this paper, we present a formal definition of the TRSP, discuss its relation with the Vehicle Routing Problem with Time Windows (VRPTW), and review related research. From a methodological perspective, we describe a matheuristic composed of a constructive heuristic, a parallel Adaptive Large Neighborhood Search, and a mathematical programming based post-optimization procedure that successfully tackles the TRSP. We validate the matheuristic on the Solomon VRPTW instances, where we achieve an average gap of 0.23% , and matched 44 out of 55 optimal solutions. Finally, we illustrate how the matheuristic successfully solves a set of TRSP instances extended from the Solomon benchmark.

The Technician Routing and Scheduling Problem (TRSP) consists in routing staff to serve requests ... more The Technician Routing and Scheduling Problem (TRSP) consists in routing staff to serve requests for service, taking into account time windows, skills, tools, and spare parts. Typical applications include maintenance operations and staff routing in telecoms, public utilities, and in the health care industry. In this paper we tackle the Dynamic TRSP (D-TRSP) in which new requests appear over time. We propose a fast reoptimization approach based on a parallel Adaptive Large Neighborhood Search (pALNS) and a Multiple Plan Approach (MPA). Finally, we present computational experiments on randomly generated instances.

The present work deals with dynamic vehicle routing problems in which new customers appear during... more The present work deals with dynamic vehicle routing problems in which new customers appear during the design or execution of the routing. We propose a parallel Adaptive Large Neighborhood Search (pALNS) that produces high quality routes in a limited computational time. Then, we introduce the notion of driver inconvenience and dene a bi-objective optimization problem that minimizes the cost of routing while maintaining its consistency throughout the day.

The Technician Routing and Scheduling Problem (TRSP) deals with a limited crew of technicians K t... more The Technician Routing and Scheduling Problem (TRSP) deals with a limited crew of technicians K that serves a set of requests R. In the TRSP, each technician has a set of skills, tools, and spare parts, while requests require a subset of each. The problem is then to design a set of tours of minimal total duration such that each request is visited exactly once, within its time window, by a technician with the required skills, tools, and spare parts.

9th Metaheuristics International Conference (MIC 2011), Udine, Italy, 2011

The technician routing and scheduling problem consists in routing and scheduling a crew of techni... more The technician routing and scheduling problem consists in routing and scheduling a crew of technicians in order to attend a set of service requests, subject to skill, tool, and spare part constraints. In this study we propose a formal definition of the problem and present a constructive heuristic and a large neighborhood search optimization algorithm.

ROADEF 2012, Apr 11, 2012

Vehicle Routing Problems (VRPs) consider the operation of a fleet of vehicles that need to servic... more Vehicle Routing Problems (VRPs) consider the operation of a fleet of vehicles that need to service customer requests. The underlying problem consists in designing a set of routes that visit all customers, optimizing one or multiple objectives. Dynamic Vehicle Routing Problems (D-VRPs) are an extension of classical VRPs in which the information available to the decision maker changes or is updated dynamically.

ROADEF 2011

The Vehicle Routing Problem with Stochastic Demands (VRPSD) is a variation of the classical Capac... more The Vehicle Routing Problem with Stochastic Demands (VRPSD) is a variation of the classical Capacitated Vehicle Routing Problem (CVRP). In contrast to the deterministic CVRP, in the VRPSD the demand of each customer is modeled as a random variable and its realization is only known upon vehicle arrival to the customer site. Under this uncertain scenario, a possible outcome is that the demand of a customer ends up exceeding the remaining capacity of the vehicle, leading to a route failure. In this study we will focus on the single vehicle VRPSD in which the fleet is limited to one vehicle with finite capacity, that can execute various routes sequentially. The present work is based on an adaptation of an optimization framework developed initially for the vehicle routing problem with dynamic customers (i.e., customers appear while the vehicles are executing their routes).

ALIO-INFORMS 2010, Jun 2010

Traditional approaches for the VRPSD aim at designing a-priori robust plans that avoid potential ... more Traditional approaches for the VRPSD aim at designing a-priori robust plans that avoid potential route failures. However, the widespread and inexpensive real-time communication and geolocalization technologies have opened promising perspectives in this field. We illustrate on the VRPSD the flexibility of jMSA, a generic framework for Multiple Scenario Approach. Preliminary results show that a continuous re-optimization leads to reductions in route failures and improvements in cost efficiency.