1,187 research outputs found
Um algoritmo exato para o problema de realocação de blocos usando novos limitantes inferiores
Orientadores: Eduardo Candido Xavier, Carla Negri LintzmayerDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: O Problema de Realocação de Blocos é um problema importante em sistemas de armazenamento. Um exemplo de entrada para este problema consiste em um conjunto de blocos distribuídos em pilhas, onde cada bloco é identicado por um número que representa sua prioridade de recuperação e todas as pilhas têm um mesmo limite de altura. Apenas blocos no topo de uma pilha podem ser movidos, com dois tipos de movimentos: ou um bloco é recuperado, o que ocorre quando ele tem a mais alta prioridade de recuperação entre os blocos empilhados, ou um bloco é realocado do topo de uma pilha para o topo de outra pilha. O objetivo é recuperar todos os blocos, respeitando sua prioridade de recuperação e executando o menor número de realocações. Resolver este problema é crítico em sistemas de armazenamento, pois economiza tempo e recursos operacionais. Apresentamos dois novos limitantes inferiores para o número de realocações em uma solução ótima. Implementamos um algoritmo de deepening A* usando esses limites inferiores propostos e outros limites inferiores bem conhecidos da literatura. Foi realizado um extenso conjunto de experimentos computacionais mostrando que os novos limites inferiores melhoram o desempenho do algoritmo exato, resolvendo mais instâncias otimamente do que quando usando outros limites inferiores na mesma quantidade de tempoAbstract: The Blocks Relocation Problem is an important problem in storage systems. An input instance for this problem consists of a set of blocks distributed in stacks where each block is identified by a retrieval priority number and each stack has the same maximum height limit. Only blocks at the top of a stack can be moved: either a block is retrieved, if it has the highest retrieval priority among the stacked blocks, or it is relocated to the top of another stack. The objective is to retrieve all the blocks, respecting their retrieval priority while performing the minimum number of relocations. Solving this problem is critical in storage systems because it saves operational time and resources. We present two new lower bounds for the number of relocations of an optimal solution. We implemented an iterative deepening A* algorithm using these new proposed lower bounds and other well- known lower bounds from the literature. We performed an extensive set of computational experiments showing that the new lower bounds improve the performance of the exact algorithm, solving to optimality more instances than when using other lower bounds in the same amount of timeMestradoCiência da ComputaçãoMestre em Ciência da ComputaçãoCAPE
Solving the unit-load pre-marshalling problem in block stacking storage systems with multiple access directions
Block stacking storage systems are highly adaptable warehouse systems with
low investment costs. With multiple, deep lanes they can achieve high storage
densities, but accessing some unit loads can be time-consuming. The unit-load
pre-marshalling problem sorts the unit loads in a block stacking storage system
in off-peak time periods to prepare for upcoming orders. The goal is to find a
minimum number of unit-load moves needed to sequence a storage bay in ascending
order based on the retrieval priority group of each unit load. In this paper,
we present two solution approaches for determining the minimum number of
unit-load moves. We show that for storage bays with one access direction, it is
possible to adapt existing, optimal tree search procedures and lower bound
heuristics from the container pre-marshalling problem. For multiple access
directions, we develop a novel, two-step solution approach based on a network
flow model and an A* algorithm with an adapted lower bound that is applicable
in all scenarios. We further analyze the performance of the presented solutions
in computational experiments for randomly generated problem instances and show
that multiple access directions greatly reduce both the total access time of
unit loads and the required sorting effort
Application of general semi-infinite Programming to Lapidary Cutting Problems
We consider a volume maximization problem arising in gemstone cutting industry. The problem is formulated as a general semi-infinite program (GSIP) and solved using an interiorpoint method developed by Stein. It is shown, that the convexity assumption needed for the convergence of the algorithm can be satisfied by appropriate modelling. Clustering techniques are used to reduce the number of container constraints, which is necessary to make the subproblems practically tractable. An iterative process consisting of GSIP optimization and adaptive refinement steps is then employed to obtain an optimal solution which is also feasible for the original problem. Some numerical results based on realworld data are also presented
Book of abstracts of the 24th Euro Working Group on Transportation Meeting
Sem resumo disponível.publishe
An Empirical Investigation Of Information Technology Mediated Customer Services In China
Information technology mediated customer service is a reality of the 21st century. More and more companies have moved their customer services from in store and in person to online through computer or mobile devices. Using 208 respondents collected from two Chinese universities, this paper investigates customer preference over two service delivery model (either in store or online) on five type of purchasing (retail, eating-out, banking, travel and entertainment) and their perception difference in customer service quality between those two delivery model. Results show that a majority of Chinese students prefer in store and in person for eating out. For ordering tickets for travel and entertainment, they prefer computer/mobile device. For retail purchasing and banking, less than half of the students prefer in person services. In general, the results show that ordering through computer/mobile devices has become more popular in China and has received higher rating for most of customer service quality except security compared to ordering in store. In addition, it is found that there exist a gender difference in purchasing preference and perception in service delivery quality in China
Recommended from our members
Continually improving grounded natural language understanding through human-robot dialog
As robots become ubiquitous in homes and workplaces such as hospitals and factories, they must be able to communicate with humans. Several kinds of knowledge are required to understand and respond to a human's natural language commands and questions. If a person requests an assistant robot to take me to Alice's office, the robot must know that Alice is a person who owns some unique office, and that take me means it should navigate there. Similarly, if a person requests bring me the heavy, green mug, the robot must have accurate mental models of the physical concepts heavy, green, and mug. To avoid forcing humans to use key phrases or words robots already know, this thesis focuses on helping robots understanding new language constructs through interactions with humans and with the world around them. To understand a command in natural language, a robot must first convert that command to an internal representation that it can reason with. Semantic parsing is a method for performing this conversion, and the target representation is often semantic forms represented as predicate logic with lambda calculus. Traditional semantic parsing relies on hand-crafted resources from a human expert: an ontology of concepts, a lexicon connecting language to those concepts, and training examples of language with abstract meanings. One thrust of this thesis is to perform semantic parsing with sparse initial data. We use the conversations between a robot and human users to induce pairs of natural language utterances with the target semantic forms a robot discovers through its questions, reducing the annotation effort of creating training examples for parsing. We use this data to build more dialog-capable robots in new domains with much less expert human effort (Thomason et al., 2015; Padmakumar et al., 2017). Meanings of many language concepts are bound to the physical world. Understanding object properties and categories, such as heavy, green, and mug requires interacting with and perceiving the physical world. Embodied robots can use manipulation capabilities, such as pushing, picking up, and dropping objects to gather sensory data about them. This data can be used to understand non-visual concepts like heavy and empty (e.g. get the empty carton of milk from the fridge), and assist with concepts that have both visual and non-visual expression (e.g. tall things look big and also exert force sooner than short things when pressed down on). A second thrust of this thesis focuses on strategies for learning these concepts using multi-modal sensory information. We use human-in-the-loop learning to get labels between concept words and actual objects in the environment (Thomason et al., 2016, 2017). We also explore ways to tease out polysemy and synonymy in concept words (Thomason and Mooney, 2017) such as light, which can refer to a weight or a color, the latter sense being synonymous with pale. Additionally, pushing, picking up, and dropping objects to gather sensory information is prohibitively time-consuming, so we investigate strategies for using linguistic information and human input to expedite exploration when learning a new concept (Thomason et al., 2018). Finally, we build an integrated agent with both parsing and perception capabilities that learns from conversations with users to improve both components over time. We demonstrate that parser learning from conversations (Thomason et al., 2015) can be combined with multi-modal perception (Thomason et al., 2016) using predicate-object labels gathered through opportunistic active learning (Thomason et al., 2017) during those conversations to improve performance for understanding natural language commands from humans. Human users also qualitatively rate this integrated learning agent as more usable after it has improved from conversation-based learning.Computer Science
- …