Three-axes rotation algorithm for the relaxed 3L-CVRP

The purpose of this work is to present a developed three-axes rotation algorithm to improve the solving methodology for the relaxed 3L-CVRP (Three-Dimensional Capacitated Vehicle Routing Problem). Although there are reported works on solving approaches for the relaxed 3L-CVRP that consider product rotation to optimize load capacity, rotation on the three axes has not been thoroughly studied. In this aspect, the present work explicitly explores the three-axes rotation and its impact on load capacity optimization. In order to improve the relaxed 3L-CVRP problem, a two-phase solution was developed. The first phase consists of finding the solution for the CVRP problem, using a demand previously obtained with a heuristic developed to convert the 3L-CVRP demand into CVRP demand. The second phase is to obtain the loading of the vehicle using a heuristic developed to load the items using rules to obtain the rotation of the items. The proposed approach was able to improve the load assignment in 48.1% of well-known 3L-CVRP instances when compared to similar approaches on the relaxed 3L-CVRP. The outcomes of this research can be applied to transportation problems where package rotation on the z-axis is an option, and there are not fragile items to load in the vehicles

Solving the Pickup and Delivery Problem with 3D Loading Constraints and Reloading Ban

In this paper, we extend the classical Pickup and Delivery Problem (PDP) to an integrated routing and three-dimensional loading problem, called PDP with 3D loading constraints (3L-PDP). A set of routes of minimum total length has to be determined such that each request is transported from a loading site to the corresponding unloading site. In the 3L-PDP, each request is given as a set of 3D rectangular items (boxes) and the vehicle capacity is replaced by a 3D loading space. This paper is the second one in a series of articles on 3L-PDP. In both articles we investigate which constraints will ensure that no reloading effort will occur, i.e. that no box is moved after loading and before unloading. In this paper, the focus is laid on the so-called reloading ban, a packing constraint that ensures identical placements of same boxes in different packing plans. We propose a hybrid algorithm for solving the 3L-PDP with reloading ban consisting of a routing and a packing procedure. The routing procedure modifies a well-known large neighborhood search for the 1D-PDP. A tree search heuristic is responsible for packing boxes. Computational experiments were carried out using 54 3L-PDP benchmark instances

A Multi-Start Algorithm for Solving the Capacitated Vehicle Routing Problem with Two-Dimensional Loading Constraints

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A Hybrid Algorithm for the Vehicle Routing Problem with Pickup and Delivery and 3D Loading Constraints

In this paper, we extend the classical Pickup and Delivery Problem (PDP) to an integrated routing and three-dimensional loading problem, called PDP with 3D loading constraints (3L-PDP). A set of routes of minimum total length has to be determined such that each request is transported from a loading site to the corresponding unloading site. In the 3L-PDP, each request is given as a set of 3D rectangular items (boxes) and the vehicle capacity is replaced by a 3D loading space. We investigate which constraints will ensure that no reloading effort will occur, i.e. that no box is moved after loading and before unloading. A spectrum of 3L-PDP variants is introduced with different characteristics in terms of reloading effort. We propose a hybrid algorithm for solving the 3L-PDP consisting of a routing and a packing procedure. The routing procedure modifies a well-known large neighborhood search for the 1D-PDP. A tree search heuristic is responsible for packing boxes. Computational experiments were carried out using 54 newly proposed 3L-PDP benchmark instances

The split delivery vehicle routing problem with three-dimensional loading constraints

 The Split Delivery Vehicle Routing Problem with three-dimensional loading constraints (3L-SDVRP) combines vehicle routing and three-dimensional loading with additional packing constraints. In the 3L-SDVRP splitting deliveries of customers is basically possible, i.e. a customer can be visited in two or more tours. We examine essential problem features and introduce two problem variants. In the first variant, called 3L-SDVRP with forced splitting, a delivery is only split if the demand of a customer cannot be transported by a single vehicle. In the second variant, termed 3L-SDVRP with optional splitting, splitting customer deliveries can be done any number of times. We propose a hybrid algorithm consisting of a local search algorithm for routing and a genetic algorithm and several construction heuristics for packing. Numerical experiments are conducted using three sets of instances with both industrial and academic origins. One of them was provided by an automotive logistics company in Shanghai; in this case some customers per instance have a total freight volume larger than the loading space of a vehicle. The results prove that splitting deliveries can be beneficial not only in the one-dimensional case but also when goods are modeled as three-dimensional items

An effective tabu search approach with improved loading algorithms for the 3L-CVRP

Computers and Operations Research55127-14

Hybrid Algorithms for the Vehicle Routing Problem with Pickup and Delivery and Two-dimensional Loading Constraints

We extend the classical Pickup and Delivery Problem (PDP) to an integrated routing and two-dimensional loading problem, called PDP with two-dimensional loading constraints (2L-PDP). A set of routes of minimum total length has to be determined such that each request is transported from a loading site to the corresponding unloading site. Each request consists of a given set of 2D rectangular items with a certain weight. The vehicles have a weight capacity and a rectangular two-dimensional loading area. All loading and unloading operations must be done exclusively by movements parallel to the longitudinal axis of the loading area of a vehicle and without moving items of other requests. Furthermore, each item must not be moved after loading and before unloading. The problem is of interest for the transport of rectangular-shaped items that cannot be stacked one on top of the other because of their weight, fragility or large dimensions. The 2L-PDP also generalizes the well-known Capacitated Vehicle Routing Problem with Two-dimensional Loading Constraints (2L-CVRP), in which the demand of each customer is to be transported from the depot to the customer’s unloading site.This paper proposes two hybrid algorithms for solving the 2L-PDP and each one consists of a routing and a packing procedure. Within both approaches, the routing procedure modifies a well-known large neighborhood search for the one-dimensional PDP and the packing procedure uses six different constructive heuristics for packing the items. Computational experiments were carried out using 60 newly proposed 2L-PDP benchmark instances with up to 150 requests

Sistema Inteligente de Recolha de Resíduos

Os problemas de planeamento de rotas de veículos, amplamente estudados na literatura, têm uma aplicabilidade real na sociedade. Na recolha de resíduos urbanos pretende-se, por um lado, otimizar a capacidade de transporte dos veículos, e por outro, minimizar a distância por estes percorrida. Deste modo, pretende-se realizar o menor número de rotas possíveis e que garantam a recolha de todos os contentores. Os modelos matemáticos de otimização linear para o problema de encaminhamento de veículos garantem soluções ótimas para a definição de rotas utilizadas na recolha de resíduos, no entanto podem ser computacionalmente difíceis de executar. Na presente investigação foram aplicados métodos de Inteligência Artificial para prever a capacidade ocupada no contentor e, com base nessa previsão, calcular as rotas mais eficientes para efetuar a recolha dos resíduos urbanos, considerando apenas os contentores identificados para recolha. Para isso, foram realizadas comparações entre diversos modelos de Machine Learning, procedendo-se também a ajustes dos respetivos hiper-parâmetros, de forma a obter uma solução eficiente para o cálculo da ocupação nos respetivos contentores. Para o cálculo da rota foram implementadas diferentes abordagens exatas e heurísticas do problema de planeamento de rotas de veículos, de modo a decidir e implementar a melhor abordagem. Como objetivo global desta dissertação, pretende-se apresentar uma boa solução, ou seja, bons tempos computacionais e uma gestão da recolha de resíduos mais eficiente e económica.Vehicle route planning problems, widely studied in the literature, have real applicability in society. In the collection of urban waste, it is intended, on the one hand, to optimize the transport capacity of vehicles, and on the other, to minimize the distance traveled by them. In this way, it is intended to carry out the fewest possible routes and to guarantee the collection of all containers. The linear optimization mathematical models for the vehicle routing problem guarantee optimal solutions for the definition of routes used in waste collection, however they can be computationally difficult to execute. In the present investigation, Artificial Intelligence methods were applied to predict the occupied capacity in the container and, based on this prediction, calculate the most efficient routes to carry out the collection of urban waste, considering only the containers identified for collection. For this, comparisons were made between different models of Machine Learning, also proceeding with the adjustments of the respective hyper-parameters, in order to obtain an efficient solution for the calculation of the occupancy in the respective containers. For the route calculation, different exact and heuristic approaches to the vehicle route planning problem were implemented, in order to decide and implement the best approach. As a global objective of this dissertation, it is intend to present a good solution, that is, good computational times and a more efficient and economical waste collection management

A memory-integrated artificial bee algorithm for heuristic optimisation

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Master of Science by ResearchAccording to studies about bee swarms, they use special techniques for foraging and they are always able to find notified food sources with exact coordinates. In order to succeed in food source exploration, the information about food sources is transferred between employed bees and onlooker bees via waggle dance. In this study, bee colony behaviours are imitated for further search in one of the common real world problems. Traditional solution techniques from literature may not obtain sufficient results; therefore other techniques have become essential for food source exploration. In this study, artificial bee colony (ABC) algorithm is used as a base to fulfil this purpose. When employed and onlooker bees are searching for better food sources, they just memorize the current sources and if they find better one, they erase the all information about the previous best food source. In this case, worker bees may visit same food source repeatedly and this circumstance causes a hill climbing in search. The purpose of this study is exploring how to embed a memory system in ABC algorithm to avoid mentioned repetition. In order to fulfil this intention, a structure of Tabu Search method -Tabu List- is applied to develop a memory system. In this study, we expect that a memory system embedded ABC algorithm provides a further search in feasible area to obtain global optimum or obtain better results in comparison with classic ABC algorithm. Results show that, memory idea needs to be improved to fulfil the purpose of this study. On the other hand, proposed memory idea can be integrated other algorithms or problem types to observe difference

Análise do sistema logístico de uma empresa do setor de bebidas : uma abordagem metodológica para integrar armazenagem e distribuição física

O cenário desafiador imposto por acontecimentos como concorrência crescente no mercado global, maior complexidade dos produtos e aspiração constante à redução de custos motivou as empresas a buscarem rapidez de resposta, como forma de diferenciação. Num contexto em que o nível de serviço prestado ao cliente se faz tão importante, a logística adquire um papel estratégico. Em lugar de otimizar pontualmente as operações, considerando os processos logísticos como meros geradores de custo, as empresas pertencentes à cadeia de suprimentos passaram a buscar novas soluções, utilizando a logística como pivô para ganhar competitividade na introdução de novos negócios. Este trabalho tem como objetivo analisar, de forma integrativa, impactos do processo de armazenagem em indicadores de distribuição física, em uma empresa distribuidora de bebidas, localizada em Sapucaia do Sul. Para tal, ele propõe uma nova metodologia de montagem de pedidos, bem como adaptações tecnológicas no processo de armazenagem como forma de melhorar indicadores de jornada de trabalho, devolução e aderência à roteirização. A partir da revisão bibliográfica referente à cadeia logística, contextualiza os procedimentos referentes ao armazém e à distribuição física, bem como focaliza na abordagem integrativa entre roteirização e carregamento, estratificando diversos modelos presentes na literatura. Através de análise de dados referentes a outros estudos, observa a falta de correlação entre aspectos de distribuição e indicadores de aderência ao tracking, aderência ao roadshow, devolução e jornada de trabalho. Observa a falta de integração entre a roteirização e as particularidades de carregamento impostas pelos fatores externos. A partir disso descreve a metodologia já citada, bem como propõe alterações no algoritmo de roteirização, na ordem de carregamento de produto, no design da frota e nos módulos do sistema de gerenciamento de armazém utilizados pela empresa, como sugestões de melhoria. Como resultado, discute vantagens e desvantagens da aplicação da metodologia proposta, ponderando os impactos gerados em parâmetros de custo, produtividade, performance e qualidade de vida. Por fim, indica a adaptação do processo de armazenamento, de forma gradual, para um sistema automatizado