Mario Ruthmair

• PhD
• Optimization Support Engineer at Gurobi Optimization

We study the multi-depot split-delivery vehicle routing problem (MDSDVRP) that combines the advantages and potential cost savings of multiple depots and split deliveries and develop the first exact algorithm for this problem. We propose an integer programming formulation using a small number of decision variables and several sets of valid inequalit...

Concerns about greenhouse gas emissions and government regulations foster the use of electric vehicles. Several recently published articles study the use of electric vehicles (EVs) in node-routing problems. In contrast, this article considers EVs in the context of arc routing while also addressing practically relevant aspects that have not been add...

We study the split-delivery multi-depot vehicle routing problem (MDSDVRP) which combines the advantages and potential cost-savings of multiple depots and split-deliveries and develop the first exact algorithm for this problem. We propose an integer programming formulation using a comparably small number of decision variables and several sets of val...

Low and infrequent demand in rural areas poses a problem for public transport providers to run cost-effective services and individual car use is usually the main means of transportation. We investigate how microtransit services can be integrated with existing public transport solutions (bus, train) as a flexible shared mobility alternative in rural...

Efficiently handling last-mile deliveries becomes more and more important nowadays. Using drones to support classical vehicles allows improving delivery schedules as long as efficient solution methods to plan last-mile deliveries with drones are available. We study exact solution approaches for some variants of the traveling salesman problem with d...

Concerns about greenhouse gas emissions and government regulations foster the use of electric vehicles. Several recently published articles study the use of electric vehicles (EVs) in node-routing problems. In contrast, this article considers EVs in the context of arc routing while also addressing practically relevant aspects that have not been add...

Influence maximization aims at identifying a limited set of key individuals in a (social) network which spreads information based on some propagation model and maximizes the number of individuals reached. We show that influence maximization based on the probabilistic independent cascade model can be modeled as a stochastic maximal covering location...

Online social networks have become crucial to propagate information. Prominent use cases include marketing campaigns for products or political candidates in which maximizing the expected number of reached individuals is a common objective. The latter can be achieved by incentivizing an appropriately selected seed set of influencers that trigger an...

We study the directed network design problem with relays (DNDPR) whose aim is to construct a minimum cost network that enables the communication of a given set of origin-destination pairs. Thereby, expensive signal regeneration devices need to be placed to cover communication distances exceeding a predefined threshold. Applications of the DNDPR ari...

In a personal communication with Ruslan Sadykov from Inria, France, we found an implementation error in our code for importing the benchmark instance set MUT leading to wrong numerical results in our original article (Gouveia, Leitner, and Ruthmair, 2017). In this corrigendum we provide corrected results for all experiments on instance set MUT. The...

Online social networks have become crucial to propagate information. Prominent use cases include marketing campaigns for products or political candidates in which maximizing the expected number of reached individuals is a common objective. The latter can be achieved by incentivizing an appropriately selected seed set of influencers that trigger an...

Efficiently handling last-mile deliveries becomes more and more important nowadays. Using drones to support classical vehicles allows improving delivery schedules as long as efficient solution methods to plan last-mile deliveries with drones are available. We study exact solution approaches for some variants of the traveling salesman problem with d...

Influence maximization aims at identifying a limited set of key individuals in a (social) network which spreads information based on some propagation model and maximizes the number of individuals reached. We show that influence maximization based on the probabilistic independent cascade model can be modeled as a stochastic maximal covering location...

Extending the concept of time-space networks, layered graphs associate information about one or multiple resource state values with nodes and arcs. While integer programming formulations based on them allow to model complex problems comparably easy, their large size makes them hard to solve for non-trivial instances. We detail and classify layered...

Influence maximization problems aim to identify key players in (social) networks and are typically motivated from viral marketing. In this work, we introduce and study the Generalized Least Cost Influence Problem (GLCIP) that generalizes many previously considered problem variants and allows to overcome some of their limitations. A formulation that...

There are many ways of modeling the Asymmetric Traveling Salesman Problem (ATSP) and the related Precedence Constrained ATSP (PCATSP). In this paper we present new formulations for the two problems that result from combining precedence variable based formulations with network flow based formulations. As suggested in Gouveia and Pesneau (2006), the...

Extending the concept of time-space networks, layered graphs associate information about one or multiple resource state values with nodes and arcs. While integer programming formulations based on them allow to model complex problems comparably easy, their large size makes them hard to solve for non-trivial instances. We detail and classify layered...

In this article we consider the network design problem with relays (NDPR), which gives answers to some important strategic design questions in telecommunication network design. Given a family of origin-destination pairs and a set of existing links these questions are as follows: (1) What are the optimal locations for signal regeneration devices (re...

We study the directed network design problem with relays (DNDPR) whose aim is to construct a minimum cost network that enables the communication of a given set of origin-destination pairs. Thereby, expensive signal regeneration devices need to be placed to cover communication distances exceeding a predefined threshold. Applications of the DNDPR ari...

Influence maximization problems aim to identify key players in (social) networks and are typically motivated from viral marketing. In this work, we introduce and study the Generalized Least Cost Influence Problem (GLCIP) that generalizes many previously considered problem variants and allows to overcome some of their limitations. A formulation that...

In this paper we study integer linear programming models and develop branch-and-cut algorithms to solve the Black-and-White Traveling Salesman Problem (BWTSP) (M. Bourgeois, G. Laporte, and F. Semet. Heuristics for the black and white traveling salesman problem. Computers & Operations Research, 30:75–85, 2003.) which is a variant of the well known...

In this article we consider the Network Design Problem with Relays (NDPR) which gives answers to some important strategic design questions in telecommunication network design and electric mobility. Given a family of origin-destination pairs and a set of existing links in the telecommunication context these questions are: (1) What are the optimal lo...

We propose and solve a rich, bi-objective extension of the orienteering problem with time windows (OPTW) to model a combined routing and scheduling problem. Our research is motivated by the problem faced by mobile freelancers who have to integrate irregular appointments and tasks into their daily routines. Those people have a number of tasks which...

Urban railway transportation organization is a systematic activity that is usually composed of several stages, including network design, line planning, timetabling, rolling stock and staffing. In this paper, we study the optimization of first train timetables for an urban railway network that focuses on designing convenient and smooth timetables fo...

Car-sharing systems are increasingly employing environmentally-friendly electric vehicles. The design and management of Ecar-sharing systems poses several additional challenges with respect to those based on traditional combustion vehicles, mainly related with the limited autonomy allowed by current battery technology. We review the main optimizati...

We present a sensitivity analysis for a mechanical model, which is used to estimate the energy demand of battery electric vehicles. This model is frequently used in literature, but its parameters are often chosen incautiously, which can lead to inaccurate energy demand estimates. We provide a novel prioritization of parameters and quantify their im...

Lecture notes

Recently, electric vehicles are gaining importance which helps to reduce dependency on oil, increases energy efficiency of transportation, reduces carbon emissions and noise, and avoids tail pipe emissions. Because of short daily driving distances, high mileage, and intermediate waiting time, fossil-fuelled taxi vehicles are ideal candidates for be...

Neste trabalho apresenta-se um modelo de fluxo, assim como alguns resultados com-putacionais, para o Electric Traveling Salesman Problem, que é uma generalização do clássico Traveling Salesman Problem em que o veículo utilizado tem um motor eléctrico. Assume-se que o nível máximo de energia na bateria do veículo eléctrico pode tornar a rota dada pe...

This book constitutes the refereed proceedings of the 7th International Conference on Computational Logistics, ICCL 2016, held in Lisbon, Portugal, in September 2016. The 29 papers presented in this volume were carefully reviewed and selected for inclusion in the book. They are organized in topical sections entitled: container terminals and maritim...

We investigate a so far not examined problem called the Interdependent Lock Scheduling Problem. A Variable Neighborhood Search approach is proposed for finding lock schedules along the Austrian part of the Danube River in order to minimize the overall ship travel times. In computational experiments the performance of our approach is assessed and co...

We address the one-to-one multi-commodity pickup and delivery traveling salesman problem (m-PDTSP) which is a generalization of the TSP and arises in several transportation and logistics applications. The objective is to find a minimum-cost directed Hamiltonian path which starts and ends at given depot nodes and such that the demand of each given c...

In this paper, we introduce and study a generalization of the degree constrained minimum spanning tree problem where we may install one of several available transmission systems (each with a different cost value) in each edge. The degree of the endnodes of each edge depends on the system installed on the edge. We also discuss a particular case that...

We consider a rather generic class of network design problems in which a set or subset of given terminal nodes must be connected to a dedicated root node by simple paths and a variety of resource and/or quality of service constraints must be respected. These extensions of the classical Steiner tree problem on a graph can be well modeled by a path f...

We present mixed integer programming approaches for optimally solving a combinatorial optimization problem arising in network design with additional quality of service constraints. The rooted delay- and delay-variation-constrained Steiner tree problem asks for a cost-minimal Steiner tree satisfying delay-constraints from source to terminals and a m...

This work deals with the application of metaheuristics to the fuel consumption minimization problem of hybrid electric vehicles (HEV) considering exactly specified driving cycles. A genetic algorithm, a downhill-simplex method and an algorithm based on swarm intelligence are used to find appropriate parameter values aiming at fuel consumption minim...

We present a layered graph model for delay-constrained minimum tree problems with a polynomial number of constraints which can be solved well for instances with low- to medium-sized sets of achievable delay values and not too high bounds. Layered graph models have been recently shown to frequently yield tight bounds in the context of hop- or delay-...

We consider the rooted delay-constrained Steiner tree problem which arises for example in the design of centralized multicasting networks where quality of service constraints are of concern. We present a path based integer linear programming formulation which has already been considered in the literature for the spanning tree variant. Solving its l...

The rooted delay-constrained minimum spanning tree problem is an NP-hard combinatorial optimization problem. The problem appears in practice for example when designing a distribution network with a guarantee of timely delivery. Another example is be a centralized broadcasting network where the delaybound represents a quality of service constraint....

We present a memetic algorithm for a combinatorial optimization problem called rooted delay-constrained minimum spanning tree problem arising for example in centralized broadcasting networks where quality of service constraints are of concern. The memetic algorithm is based on a specialized solution representation and a simple and effective decodin...

We consider the rooted delay-constrained Steiner tree problem which arises, e.g., in the design of centralized multicasting networks where quality of service constraints are of concern. We present a mixed integer linear programming formulation based on the concept of feasible paths which has already been considered in the literature for the spannin...

The rooted delay-constrained minimum spanning tree prob- lem is an NP-hard combinatorial optimization problem arising for ex- ample in the design of centralized broadcasting networks where quality of service constraints are of concern. We present two new approaches to solve this problem heuristically following the concepts of ant colony opti- mizat...

A Video-on-Demand system usually consists of a large num- ber of independent video servers. In order to utilize network resources as eciently as possible the overall network load should be balanced among the available servers. We consider a problem formulation based on an estimation of the expected number of requests per movie dur- ing the period o...

The rooted delay-constrained minimum spanning tree prob- lem is an NP-hard combinatorial optimization problem arising for exam- ple in the design of centralized broadcasting networks where quality of service constraints are of concern. We present a construction heuristic based on Kruskal's algorithm for finding a minimum cost spanning tree which el...