Roberto Montemanni - Academia.edu (original) (raw)
Papers by Roberto Montemanni
… Workshop on Freight …, 2003
Most of the literature available on vehicle routing problems is about static problems, where all ... more Most of the literature available on vehicle routing problems is about static problems, where all data are known in advance. The technological advances of the last few years rise a new class of problems about dynamic vehicle routing, where new orders are received as time progresses and must be dynamically incorporated into an evolving schedule. In this work an algorithm for this problem, based on the Ant Colony System paradigm, is proposed. Computational results on some problems derived from widely-available benchmarks confirm the efficiency of the method we propose. A realistic case study, based on the road network of the city of Lugano (Switzerland) will be finally presented. * The full paper is available as Montemanni et al. [6].
Foundations of Computing and Decision Sciences, 2009
This paper discusses a heuristic approach for Team Orienteering Problems with Time Windows. The m... more This paper discusses a heuristic approach for Team Orienteering Problems with Time Windows. The method we propose takes advantage of a solution model based on a hierarchic generalization of the original problem, which is combined with an Ant Colony System algorithm. Computational results on benchmark instances previously adopted in the literature suggest that the algorithm we propose is effective in practice.
This paper discusses a heuristic approach for Team Orienteering Problems with Time Windows. The m... more This paper discusses a heuristic approach for Team Orienteering Problems with Time Windows. The method we propose takes advantage of a solution model based on a hierarchic generalization of the original problem, which is combined with an Ant Colony System algorithm. Computational results on benchmark instances previously adopted in the literature suggest that the algorithm we propose is effective in practice.
Algorithms
Manual order picking, the process of retrieving stock keeping units from their storage location t... more Manual order picking, the process of retrieving stock keeping units from their storage location to fulfil customer orders, is one of the most labour-intensive and costly activity in modern supply chains. To improve the outcome of order picking systems, automated and robotized components are increasingly introduced creating hybrid order picking systems where humans and machines jointly work together. This study focuses on the application of a hybrid picker-to-parts order picking system, in which human operators collaborate with Automated Mobile Robots (AMRs). In this paper a warehouse with a two-blocks layout is investigated. The main contributions are new mathematical models for the optimization of picking operations and synchronizations. Two alternative implementations for an AMR system are considered. In the first one handover locations, where pickers load AMRs are shared between pairs of opposite sub-aisles, while in the second they are not. It is shown that solving the mathemati...
2018 Joint 10th International Conference on Soft Computing and Intelligent Systems (SCIS) and 19th International Symposium on Advanced Intelligent Systems (ISIS)
The Probabilistic Orienteering Problem is a stochastic optimization problem about the delivery or... more The Probabilistic Orienteering Problem is a stochastic optimization problem about the delivery or goods to customers. Only a subset of the customer can be served in the given time, so the problem consists in the selection of the customers providing more revenues and in the optimization of a truck tour to serve them. The presence of the customers is however stochastic, and this has to be taken into account while evaluating the objective function of each solution. Due to the high computational complexity of such an objective function, Monte Carlo sampling method is used to estimate it in a fast way. There is one crucial parameter in a Monte Carlo sampling evaluator which is the number of samples to be used. More samples mean high precision, less samples mean high speed. An instance-dependent trade-off has to be found. The topic of this paper is a Machine Learning-based method to estimate the best number of samples, given the characteristics of an instance. Two methods are presented and compared from an experimental point of view. In particular, it is shown that a less intuitive and slightly more complex method is able to provide more precise estimations.
Journal of the Operations Research Society of China
The paper discusses an enhancement to a recently presented supervised learning algorithm to solve... more The paper discusses an enhancement to a recently presented supervised learning algorithm to solve the Maximum Independent Set problem. In particular, it is shown that the algorithm can be improved by simplifying the task learnt by the neural network adopted, with measurable effects on the quality of the solutions provided on unseen instances. Empirical results are presented to validate the idea
Journal of Optimization Theory and Applications
This paper explores a new approach to reduce the maximum clique problem associated with permutati... more This paper explores a new approach to reduce the maximum clique problem associated with permutation Hamming graphs to smaller clique problems. The vertices of a permutation Hamming graph are permutations of n integers and the edges connect pairs of vertices at a Hamming distance greater than or equal to a threshold d. The maximum clique problem for permutation Hamming graphs is a challenging task due to the size, density and regularity of the graphs. However, symmetry properties, which are still partly unexplored, can help to reduce the problems’ size and hardness. A property of edge transitivity with respect to automorphisms is proven and leads to a classification for cycle-equivalent edges. This property enables to reduce the full-size clique problem to a set of significantly smaller (and easier to solve) clique problems. The number of reduced problems can be expressed by means of the partition function of integer numbers. Computational experiments confirm that additional knowledg...
Lecture Notes in Operations Research, Aug 2, 2021
The ML-Constructive heuristic is a recently presented method and the first hybrid method capable ... more The ML-Constructive heuristic is a recently presented method and the first hybrid method capable of scaling up to real scale traveling salesman problems. It combines machine learning techniques and classic optimization techniques. In this paper we present improvements to the computational weight of the original deep learning model. In addition, as simpler models reduce the execution time, the possibility of adding a local-search phase is explored to further improve performance. Experimental results corroborate the quality of the proposed improvements.
Information and Communication Technologies (ICTs) are connected to issues of sustainability in ma... more Information and Communication Technologies (ICTs) are connected to issues of sustainability in many ways.
Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems, 2021
The COVID-19 pandemic is changing consumer behavior and accelerating the interest for online groc... more The COVID-19 pandemic is changing consumer behavior and accelerating the interest for online grocery purchases. Hence, traditional brick-and-mortar retailers are developing omnichannel solutions enabling online purchases in parallel to normal activities. Buy-Online-Pick-up-in-Store concepts are flourishing in this context, and they are the topic of this work. In this paper we propose a novel application of the sequential ordering problem to model products picking throughout the store shelves. The result is an optimized picking sequence that however takes also into account the characteristics of the goods (fragility, weight, etc.). The aim is to preserve goods integrity while allowing the pickers to optimize their route through the shop. The approach is exemplified on historical online orders of a real German shop. © 2021, IFIP International Federation for Information Processing.
This paper introduces a new mobility platform that favours reducing individual car use, by combin... more This paper introduces a new mobility platform that favours reducing individual car use, by combining car flexibility with advantages offered by public transport, such as punctuality, comfort, safety and low environmental impact. Such platform services are delivered by means of a smartphone app that, thanks to advanced artificial intelligence algorithms, performs multimodal vehicle routing by accounting for walking, public transport and car-pooling rides. To explore citizens’ attitudes and perceptions towards SocialCar, and assess its overall business potential, we tested a prototype version in Canton Ticino (Southern Switzerland), engaging common citizens and their everyday mobility needs. In this paper we first present the app and the route planning algorithms we developed to match travel demand and offer, commenting on the challenges to be addressed when using real-life data (shortcomings in mapping, public transport and car-pooling data). Then, we describe the methodology used to...
Algorithms, 2021
Online shopping is growing fast due to the increasingly widespread use of digital services. Durin... more Online shopping is growing fast due to the increasingly widespread use of digital services. During the COVID-19 pandemic, the desire for contactless shopping has further changed consumer behavior and accelerated the acceptance of online grocery purchases. Consequently, traditional brick-and-mortar retailers are developing omnichannel solutions such as click-and-collect services to fulfill the increasing demand. In this work, we consider the Buy-Online-Pick-up-in-Store concept, in which online orders are collected by employees of the conventional stores. As labor is a major cost driver, we apply and discuss different optimizing strategies in the picking and packing process based on real-world data from a German retailer. With comparison of different methods, we estimate the improvements in efficiency in terms of time spent during the picking process. Additionally, the time spent on the packing process can be further decreased by applying a mathematical model that guides the employees...
Algorithms, 2021
Recent systems applying Machine Learning (ML) to solve the Traveling Salesman Problem (TSP) exhib... more Recent systems applying Machine Learning (ML) to solve the Traveling Salesman Problem (TSP) exhibit issues when they try to scale up to real case scenarios with several hundred vertices. The use of Candidate Lists (CLs) has been brought up to cope with the issues. A CL is defined as a subset of all the edges linked to a given vertex such that it contains mainly edges that are believed to be found in the optimal tour. The initialization procedure that identifies a CL for each vertex in the TSP aids the solver by restricting the search space during solution creation. It results in a reduction of the computational burden as well, which is highly recommended when solving large TSPs. So far, ML was engaged to create CLs and values on the elements of these CLs by expressing ML preferences at solution insertion. Although promising, these systems do not restrict what the ML learns and does to create solutions, bringing with them some generalization issues. Therefore, motivated by explorator...
Computers & Operations Research, 2021
This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Algorithms, 2020
Let G=(V,E) be an undirected graph with vertex set V and edge set E. A clique C of G is a subset ... more Let G=(V,E) be an undirected graph with vertex set V and edge set E. A clique C of G is a subset of the vertices of V with every pair of vertices of C adjacent. A maximum clique is a clique with the maximum number of vertices. A tabu search algorithm for the maximum clique problem that uses an exact algorithm on subproblems is presented. The exact algorithm uses a graph coloring upper bound for pruning, and the best such algorithm to use in this context is considered. The final tabu search algorithm successfully finds the optimal or best known solution for all standard benchmarks considered. It is compared with a state-of-the-art algorithm that does not use exact search. It is slower to find the known optimal solution for most instances but is faster for five instances and finds a larger clique for two instances.
The Electronic Journal of Combinatorics, 2012
In recent years the detailed study of the construction of constant weight codes has been extended... more In recent years the detailed study of the construction of constant weight codes has been extended from length at most 28 to lengths less than 64. Andries Brouwer maintains web pages with tables of the best known constant weight codes of these lengths. In many cases the codes have more codewords than the best code in the literature, and are not particularly easy to improve. Many of the codes are constructed using a specified permutation group as automorphism group. The groups used include cyclic, quasi-cyclic, affine general linear groups etc. sometimes with fixed points. The precise rationale for the choice of groups is not clear.In this paper the choice of groups is made systematic by the use of the classification of primitive permutation groups. Together with several improved techniques for finding a maximum clique, this has led to the construction of 39 improved constant weight codes.
Millenium - Journal of Education, Technologies, and Health, 2019
RESUMO Introdução: O Problema de projeto de viagem turística é uma variante de um problema de pla... more RESUMO Introdução: O Problema de projeto de viagem turística é uma variante de um problema de planeamento de rotas para turistas interessados em vários pontos de interesse. Cada ponto de interesse tem disponibilidades diferentes e um certo índice de satisfação pode ser alcançado quando é visitado. Objetivos: O objetivo é selecionar um subconjunto de pontos de interesse a visitar dentro de um determinado orçamento de tempo, de modo que a pontuação de satisfação do turista seja maximizada e o tempo total de viagem seja minimizado. Métodos: No modelo proposto, o cálculo da disponibilidade de um PI é baseado no tempo de espera e / ou na previsão do tempo. No entanto, pesquisas mostram que a maioria dos turistas prefere viajar dentro de uma área lotada e limitada de PIs muito atraentes por razões de segurança e porque sentem um maior controlo. Resultados: Neste trabalho, demonstramos que o modelo existente do Problema de Orientação Probabilística se encaixa em uma variante probabilística desse problema e que as técnicas de Amostragem de Monte Carlo podem ser usadas dentro de um solucionador de heurísticas para fornecer soluções com eficiência. Conclusões: Neste trabalho demonstramos que o modelo existente do Problema Probabilístico de Orientação se encaixa no Problema Estocástico de Projeto de Viagem Turística. Propusemos uma maneira de resolver o problema usando técnicas de Amostragem de Monte Carlo num solucionador heurístico e discutimos várias possíveis melhorias no modelo. Uma extensão adicional do modelo será desenvolvida para solucionar problemas mais práticos, no futuro.
International Journal of Metaheuristics, 2019
A hybrid algorithm for the maximum clique problem is presented. A heuristic is used to generate c... more A hybrid algorithm for the maximum clique problem is presented. A heuristic is used to generate cliques and these are improved by some simple optimizations and tabu search. All components of the algorithm make use of a pseudoexact algorithm, which is an exact algorithm with some specialized pruning. Preprocessing is useful for some instances. The algorithm is shown to be successful using standard and new benchmarks.
Journal of Traffic and Logistics Engineering, 2017
SocialCar is a research project that aims at integrating carpooling with traditional transportati... more SocialCar is a research project that aims at integrating carpooling with traditional transportation systems in urban areas, while benefiting from social media to enhance the user's experience. The system is based on route planning and ride matching algorithms to provide the users with alternatives for their trips. In this work, we overview the multiple approaches in the literature to model transportation networks and carpooling services, and a route planning algorithm which integrates multiple transportation types together. Finally, the performance measures of the route planner are reported.
… Workshop on Freight …, 2003
Most of the literature available on vehicle routing problems is about static problems, where all ... more Most of the literature available on vehicle routing problems is about static problems, where all data are known in advance. The technological advances of the last few years rise a new class of problems about dynamic vehicle routing, where new orders are received as time progresses and must be dynamically incorporated into an evolving schedule. In this work an algorithm for this problem, based on the Ant Colony System paradigm, is proposed. Computational results on some problems derived from widely-available benchmarks confirm the efficiency of the method we propose. A realistic case study, based on the road network of the city of Lugano (Switzerland) will be finally presented. * The full paper is available as Montemanni et al. [6].
Foundations of Computing and Decision Sciences, 2009
This paper discusses a heuristic approach for Team Orienteering Problems with Time Windows. The m... more This paper discusses a heuristic approach for Team Orienteering Problems with Time Windows. The method we propose takes advantage of a solution model based on a hierarchic generalization of the original problem, which is combined with an Ant Colony System algorithm. Computational results on benchmark instances previously adopted in the literature suggest that the algorithm we propose is effective in practice.
This paper discusses a heuristic approach for Team Orienteering Problems with Time Windows. The m... more This paper discusses a heuristic approach for Team Orienteering Problems with Time Windows. The method we propose takes advantage of a solution model based on a hierarchic generalization of the original problem, which is combined with an Ant Colony System algorithm. Computational results on benchmark instances previously adopted in the literature suggest that the algorithm we propose is effective in practice.
Algorithms
Manual order picking, the process of retrieving stock keeping units from their storage location t... more Manual order picking, the process of retrieving stock keeping units from their storage location to fulfil customer orders, is one of the most labour-intensive and costly activity in modern supply chains. To improve the outcome of order picking systems, automated and robotized components are increasingly introduced creating hybrid order picking systems where humans and machines jointly work together. This study focuses on the application of a hybrid picker-to-parts order picking system, in which human operators collaborate with Automated Mobile Robots (AMRs). In this paper a warehouse with a two-blocks layout is investigated. The main contributions are new mathematical models for the optimization of picking operations and synchronizations. Two alternative implementations for an AMR system are considered. In the first one handover locations, where pickers load AMRs are shared between pairs of opposite sub-aisles, while in the second they are not. It is shown that solving the mathemati...
2018 Joint 10th International Conference on Soft Computing and Intelligent Systems (SCIS) and 19th International Symposium on Advanced Intelligent Systems (ISIS)
The Probabilistic Orienteering Problem is a stochastic optimization problem about the delivery or... more The Probabilistic Orienteering Problem is a stochastic optimization problem about the delivery or goods to customers. Only a subset of the customer can be served in the given time, so the problem consists in the selection of the customers providing more revenues and in the optimization of a truck tour to serve them. The presence of the customers is however stochastic, and this has to be taken into account while evaluating the objective function of each solution. Due to the high computational complexity of such an objective function, Monte Carlo sampling method is used to estimate it in a fast way. There is one crucial parameter in a Monte Carlo sampling evaluator which is the number of samples to be used. More samples mean high precision, less samples mean high speed. An instance-dependent trade-off has to be found. The topic of this paper is a Machine Learning-based method to estimate the best number of samples, given the characteristics of an instance. Two methods are presented and compared from an experimental point of view. In particular, it is shown that a less intuitive and slightly more complex method is able to provide more precise estimations.
Journal of the Operations Research Society of China
The paper discusses an enhancement to a recently presented supervised learning algorithm to solve... more The paper discusses an enhancement to a recently presented supervised learning algorithm to solve the Maximum Independent Set problem. In particular, it is shown that the algorithm can be improved by simplifying the task learnt by the neural network adopted, with measurable effects on the quality of the solutions provided on unseen instances. Empirical results are presented to validate the idea
Journal of Optimization Theory and Applications
This paper explores a new approach to reduce the maximum clique problem associated with permutati... more This paper explores a new approach to reduce the maximum clique problem associated with permutation Hamming graphs to smaller clique problems. The vertices of a permutation Hamming graph are permutations of n integers and the edges connect pairs of vertices at a Hamming distance greater than or equal to a threshold d. The maximum clique problem for permutation Hamming graphs is a challenging task due to the size, density and regularity of the graphs. However, symmetry properties, which are still partly unexplored, can help to reduce the problems’ size and hardness. A property of edge transitivity with respect to automorphisms is proven and leads to a classification for cycle-equivalent edges. This property enables to reduce the full-size clique problem to a set of significantly smaller (and easier to solve) clique problems. The number of reduced problems can be expressed by means of the partition function of integer numbers. Computational experiments confirm that additional knowledg...
Lecture Notes in Operations Research, Aug 2, 2021
The ML-Constructive heuristic is a recently presented method and the first hybrid method capable ... more The ML-Constructive heuristic is a recently presented method and the first hybrid method capable of scaling up to real scale traveling salesman problems. It combines machine learning techniques and classic optimization techniques. In this paper we present improvements to the computational weight of the original deep learning model. In addition, as simpler models reduce the execution time, the possibility of adding a local-search phase is explored to further improve performance. Experimental results corroborate the quality of the proposed improvements.
Information and Communication Technologies (ICTs) are connected to issues of sustainability in ma... more Information and Communication Technologies (ICTs) are connected to issues of sustainability in many ways.
Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems, 2021
The COVID-19 pandemic is changing consumer behavior and accelerating the interest for online groc... more The COVID-19 pandemic is changing consumer behavior and accelerating the interest for online grocery purchases. Hence, traditional brick-and-mortar retailers are developing omnichannel solutions enabling online purchases in parallel to normal activities. Buy-Online-Pick-up-in-Store concepts are flourishing in this context, and they are the topic of this work. In this paper we propose a novel application of the sequential ordering problem to model products picking throughout the store shelves. The result is an optimized picking sequence that however takes also into account the characteristics of the goods (fragility, weight, etc.). The aim is to preserve goods integrity while allowing the pickers to optimize their route through the shop. The approach is exemplified on historical online orders of a real German shop. © 2021, IFIP International Federation for Information Processing.
This paper introduces a new mobility platform that favours reducing individual car use, by combin... more This paper introduces a new mobility platform that favours reducing individual car use, by combining car flexibility with advantages offered by public transport, such as punctuality, comfort, safety and low environmental impact. Such platform services are delivered by means of a smartphone app that, thanks to advanced artificial intelligence algorithms, performs multimodal vehicle routing by accounting for walking, public transport and car-pooling rides. To explore citizens’ attitudes and perceptions towards SocialCar, and assess its overall business potential, we tested a prototype version in Canton Ticino (Southern Switzerland), engaging common citizens and their everyday mobility needs. In this paper we first present the app and the route planning algorithms we developed to match travel demand and offer, commenting on the challenges to be addressed when using real-life data (shortcomings in mapping, public transport and car-pooling data). Then, we describe the methodology used to...
Algorithms, 2021
Online shopping is growing fast due to the increasingly widespread use of digital services. Durin... more Online shopping is growing fast due to the increasingly widespread use of digital services. During the COVID-19 pandemic, the desire for contactless shopping has further changed consumer behavior and accelerated the acceptance of online grocery purchases. Consequently, traditional brick-and-mortar retailers are developing omnichannel solutions such as click-and-collect services to fulfill the increasing demand. In this work, we consider the Buy-Online-Pick-up-in-Store concept, in which online orders are collected by employees of the conventional stores. As labor is a major cost driver, we apply and discuss different optimizing strategies in the picking and packing process based on real-world data from a German retailer. With comparison of different methods, we estimate the improvements in efficiency in terms of time spent during the picking process. Additionally, the time spent on the packing process can be further decreased by applying a mathematical model that guides the employees...
Algorithms, 2021
Recent systems applying Machine Learning (ML) to solve the Traveling Salesman Problem (TSP) exhib... more Recent systems applying Machine Learning (ML) to solve the Traveling Salesman Problem (TSP) exhibit issues when they try to scale up to real case scenarios with several hundred vertices. The use of Candidate Lists (CLs) has been brought up to cope with the issues. A CL is defined as a subset of all the edges linked to a given vertex such that it contains mainly edges that are believed to be found in the optimal tour. The initialization procedure that identifies a CL for each vertex in the TSP aids the solver by restricting the search space during solution creation. It results in a reduction of the computational burden as well, which is highly recommended when solving large TSPs. So far, ML was engaged to create CLs and values on the elements of these CLs by expressing ML preferences at solution insertion. Although promising, these systems do not restrict what the ML learns and does to create solutions, bringing with them some generalization issues. Therefore, motivated by explorator...
Computers & Operations Research, 2021
This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Algorithms, 2020
Let G=(V,E) be an undirected graph with vertex set V and edge set E. A clique C of G is a subset ... more Let G=(V,E) be an undirected graph with vertex set V and edge set E. A clique C of G is a subset of the vertices of V with every pair of vertices of C adjacent. A maximum clique is a clique with the maximum number of vertices. A tabu search algorithm for the maximum clique problem that uses an exact algorithm on subproblems is presented. The exact algorithm uses a graph coloring upper bound for pruning, and the best such algorithm to use in this context is considered. The final tabu search algorithm successfully finds the optimal or best known solution for all standard benchmarks considered. It is compared with a state-of-the-art algorithm that does not use exact search. It is slower to find the known optimal solution for most instances but is faster for five instances and finds a larger clique for two instances.
The Electronic Journal of Combinatorics, 2012
In recent years the detailed study of the construction of constant weight codes has been extended... more In recent years the detailed study of the construction of constant weight codes has been extended from length at most 28 to lengths less than 64. Andries Brouwer maintains web pages with tables of the best known constant weight codes of these lengths. In many cases the codes have more codewords than the best code in the literature, and are not particularly easy to improve. Many of the codes are constructed using a specified permutation group as automorphism group. The groups used include cyclic, quasi-cyclic, affine general linear groups etc. sometimes with fixed points. The precise rationale for the choice of groups is not clear.In this paper the choice of groups is made systematic by the use of the classification of primitive permutation groups. Together with several improved techniques for finding a maximum clique, this has led to the construction of 39 improved constant weight codes.
Millenium - Journal of Education, Technologies, and Health, 2019
RESUMO Introdução: O Problema de projeto de viagem turística é uma variante de um problema de pla... more RESUMO Introdução: O Problema de projeto de viagem turística é uma variante de um problema de planeamento de rotas para turistas interessados em vários pontos de interesse. Cada ponto de interesse tem disponibilidades diferentes e um certo índice de satisfação pode ser alcançado quando é visitado. Objetivos: O objetivo é selecionar um subconjunto de pontos de interesse a visitar dentro de um determinado orçamento de tempo, de modo que a pontuação de satisfação do turista seja maximizada e o tempo total de viagem seja minimizado. Métodos: No modelo proposto, o cálculo da disponibilidade de um PI é baseado no tempo de espera e / ou na previsão do tempo. No entanto, pesquisas mostram que a maioria dos turistas prefere viajar dentro de uma área lotada e limitada de PIs muito atraentes por razões de segurança e porque sentem um maior controlo. Resultados: Neste trabalho, demonstramos que o modelo existente do Problema de Orientação Probabilística se encaixa em uma variante probabilística desse problema e que as técnicas de Amostragem de Monte Carlo podem ser usadas dentro de um solucionador de heurísticas para fornecer soluções com eficiência. Conclusões: Neste trabalho demonstramos que o modelo existente do Problema Probabilístico de Orientação se encaixa no Problema Estocástico de Projeto de Viagem Turística. Propusemos uma maneira de resolver o problema usando técnicas de Amostragem de Monte Carlo num solucionador heurístico e discutimos várias possíveis melhorias no modelo. Uma extensão adicional do modelo será desenvolvida para solucionar problemas mais práticos, no futuro.
International Journal of Metaheuristics, 2019
A hybrid algorithm for the maximum clique problem is presented. A heuristic is used to generate c... more A hybrid algorithm for the maximum clique problem is presented. A heuristic is used to generate cliques and these are improved by some simple optimizations and tabu search. All components of the algorithm make use of a pseudoexact algorithm, which is an exact algorithm with some specialized pruning. Preprocessing is useful for some instances. The algorithm is shown to be successful using standard and new benchmarks.
Journal of Traffic and Logistics Engineering, 2017
SocialCar is a research project that aims at integrating carpooling with traditional transportati... more SocialCar is a research project that aims at integrating carpooling with traditional transportation systems in urban areas, while benefiting from social media to enhance the user's experience. The system is based on route planning and ride matching algorithms to provide the users with alternatives for their trips. In this work, we overview the multiple approaches in the literature to model transportation networks and carpooling services, and a route planning algorithm which integrates multiple transportation types together. Finally, the performance measures of the route planner are reported.