Container Loading Problems: A State-of-the-Art Review

Container loading is a pivotal function for operating supply chains efficiently. Underperformance results in unnecessary costs (e.g. cost of additional containers to be shipped) and in an unsatisfactory customer service (e.g. violation of deadlines agreed to or set by clients). Thus, it is not surprising that container loading problems have been dealt with frequently in the operations research literature. It has been claimed though that the proposed approaches are of limited practical value since they do not pay enough attention to constraints encountered in practice.In this paper, a review of the state-of-the-art in the field of container loading will be given. We will identify factors which - from a practical point of view - need to be considered when dealing with container loading problems and we will analyze whether and how these factors are represented in methods for the solution of such problems. Modeling approaches, as well as exact and heuristic algorithms will be reviewed. This will allow for assessing the practical relevance of the research which has been carried out in the field. We will also mention several issues which have not been dealt with satisfactorily so far and give an outlook on future research opportunities

Resolução do problema de carregamento de container e de roteamento de veículos utilizando algoritimos genéticos

Resumo: Esta dissertação aborda uma proposta de metodologia de resolução de um problema de entregas que abrange a integração de dois problemas clássicos de Otimização Combinatória: o Problema de Carregamento de Container (PCC) e o Problema de Roteamento de Veículos (PRV). O problema específico analizado está na logística empregada no carregamento e entrega de eletrodomésticos (linha branca) vendidos à pessoa física. Para representar esta situação, assume-se um cenário fictício em que a empresa que vende os produtos possui um Centro de Distribuição de Produtos (CD) localizado na cidade de Curitiba e uma lista de doze possíveis produtos a serem vendidos. A partir desta lista foram gerados 160 pedidos diferentes para serem entregues em vinte endereços aleatórios localizados também na cidade de Curitiba. Para a resolução deste problema, apresenta-se uma metodologia baseada em formação de torres de caixas e um Algoritmo Bottom-Left para realizar o carregamento dos pedidos no compartimento de carga dos veículos e um Algoritmo Genético para realizar a otimização evolutiva da solução até que se encontre uma solução suficientemente próxima à solução ótima do problema, buscando diminuir, a cada geração, a distância total percorrida pelos veículos de entrega. Para demonstração e utilização desta metodologia, apresenta-se uma implementação dos algoritmos e técnicas de pesquisa operacional descritos acima para a resolução desenvolvida em linguagem de programação Microsoft Visual Basic. Utilizando-se esta implementação e o cenário construído para testes, obteve-se bons resultados em relação à distância total percorrida pelos veículos de entrega, com redução de 25% a 45% em relação às soluções iniciais aleatórias, sendo que em alguns casos, esta melhoria alcançou até 60%

The traveling salesman problem with three-dimensional loading constraints

Orientador: Flávio Keidi MiyazawaDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Nesta dissertação de mestrado apresentamos um método exato para o Problema do Caixeiro Viajante com Restrições de Empacotamento Tridimensional, que combina o Problema do Caixeiro Viajante o Problema de Empacotamento Tridimensional com Restrição de Ordem. Neste problema, um veículo deve partir carregado de um depósito e entregar caixas em pontos pré-definidos para seus clientes. Cada cliente tem um conjunto de caixas que deve receber e o objetivo é minimizar o custo de deslocamento do veículo. As caixas devem ser retiradas a partir da porta do contêiner do veículo e a remoção das caixas de um cliente não podem ser obstruídas pelas caixas a serem descarregadas posteriormente. Propomos uma abordagem exata baseada em branch-and-cut para buscar uma rota de custo mínimo. Apresentamos algumas adaptações de algoritmos da literatura e uma formulação em Programação por Restrições para encontrar um empacotamento que obedece restrições de ordem. Realizamos testes computacionais em instâncias geradas aleatoriamente e comparamos resultados com os algoritmos adaptados da literatura. Os resultados foram bastante satisfatórios resolvendo instâncias de tamanho médio em tempo computacional aceitável na práticaAbstract: We present an exact method for the Traveling Salesman Problem with Three-dimensional Loading Constraints. This problem combines the Traveling Salesman Problem, and the Three- Dimensional Packing Problem With Loading Constraints. In this problem, a vehicle must be loaded at the depot and deliver boxes to the customers. Every customer has a set of boxes that should receive and our goal is to minimize the travel cost of the vehicle. Unloading is done through a single side of the container and items from an unloading customer must not be blocked by items to be delivered later. We propose exact and heuristic branch-and-cut algorithm to find a minimum cost route. Adaptations of algorithms from the literature and a Constraint Programming formulation is presented to find a packing that consider unloading contraints. We performed computational tests on instances randomly generated and compared results with the algorithms adapted from literature. The results were quite satisfactory resolving several instances in reasonable computational timeMestradoCiência da ComputaçãoMestre em Ciência da Computaçã

The Air Cargo Load Planning Problem

A major operational planning problem in the air cargo industry is how to arrange cargo in an aircraft to fly safely and profitably. Therefore, a challenging planning puzzle has to be solved for each flight. Besides its complexity, the planning is mostly done manually today, which is a time consuming process with uncertain solution quality. The literature on loading problems in an air cargo context is scarce and the term is used ambiguously for different subproblems like selecting containers, packing items into containers, or loading containers into aircraft. All of the presented models only focus on certain aspects of what is in practice a larger planning problem. Additionally, some practical aspects have not been covered in the literature. In this work, we provide a comprehensive overview of the air cargo load planning problem as seen in the operational practice of our industrial partner. We formalize its requirements and the objectives of the respective stakeholders. Furthermore, we develop and evaluate suitable solution approaches. Therefore, we decompose the problem into four steps: aircraft configuration, build-up scheduling, air cargo palletization, and weight and balance. We solve these steps by employing mainly mixed-integer linear programming. Two subproblems are further decomposed by adding a rolling horizon planning approach and a Logic-based Benders Decomposition (LBBD). The actual three-dimensional packing problem is solved as a constraint program in the subproblem of the LBBD. We evaluated our approaches on instances containing 513 real and synthetic flights. The numerical results show that the developed approaches are suitable to automatically generate load plans for cargo flights. Compared to load plans from practice, we could achieve a 20 percent higher packing density and significantly reduce the handling effort in the air cargo terminal. The achieved costs of additional fuel burn due to aircraft imbalances and reloading operations at stop-over airports are almost negligible. The required runtimes range between 13 and 38 minutes per flight on standard hardware, which is acceptable for non-interactive planning. Cargo airlines can significantly profit from employing the developed approaches in their operational practice. More and especially the profitable last-minute cargo can be transported. Furthermore, the costs of load planning, handling effort, and aircraft operations can be significantly reduced

Operational Research IO2017, Valença, Portugal, June 28-30

This proceedings book presents selected contributions from the XVIII Congress of APDIO (the Portuguese Association of Operational Research) held in Valença on June 28–30, 2017. Prepared by leading Portuguese and international researchers in the field of operations research, it covers a wide range of complex real-world applications of operations research methods using recent theoretical techniques, in order to narrow the gap between academic research and practical applications. Of particular interest are the applications of, nonlinear and mixed-integer programming, data envelopment analysis, clustering techniques, hybrid heuristics, supply chain management, and lot sizing and job scheduling problems. In most chapters, the problems, methods and methodologies described are complemented by supporting figures, tables and algorithms. The XVIII Congress of APDIO marked the 18th installment of the regular biannual meetings of APDIO – the Portuguese Association of Operational Research. The meetings bring together researchers, scholars and practitioners, as well as MSc and PhD students, working in the field of operations research to present and discuss their latest works. The main theme of the latest meeting was Operational Research Pro Bono. Given the breadth of topics covered, the book offers a valuable resource for all researchers, students and practitioners interested in the latest trends in this field.info:eu-repo/semantics/publishedVersio