Design for product-embedded disassembly pathways

This paper presents a computational method for designing an assembly with multiple built-in disassembly pathways, each of which can be activated to retrieve certain components. It is motivated by the global sales of consumer products whose optimal end-of-life options vary geographically due to local recycling/reuse infrastructures and regulatory requirements. Given the sets of components to be retrieved at each location, the method simultaneously determines the spatial configurations of components and locator features, such that each set of desired components is retrieved via a domino-like self-disassembly" process triggered by the removal of a fastener. A multi-objective generic algorithm is utilized to search for Pareto-optimal designs in terms of the realization of the desired disassembly pathways, the satisfaction of distance specifications among components, the minimization of disassembly cost at each location, and the efficient use of on-component locator features. A case study demonstrates the feasibility of the method.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87258/4/Saitou77.pd

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

AgeFor: proposta de um modelo de agente inteligente baseado na metáfora dos formigueiros

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Engenharia de Produção.Cada vez mais os processos de desenvolvimento de software têm se complicado em virtude do fato da complexidade dos problemas a serem resolvidos estarem aumentando de forma bastante razoável. Para tanto, aqui está se propondo um modelo para construção de software inteligente # AgeFor # que, a partir da metáfora de como se organiza, se comporta e vive uma colônia de formigas; tenta-se criar o comportamento colaborativo, cooperativo e inteligente de agentes de software

Evolutionary Algorithms Based on Effective Search Space Reduction for Financial Optimization Problems

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2015. 8. 문병로.This thesis presents evolutionary algorithms incorporated with effective search space reduction for financial optimization problems. Typical evolutionary algorithms try to find optimal solutions in the original, or unrestricted search space. However, they can be unsuccessful if the optimal solutions are too complex to be discovered from scratch. This can be relieved by restricting the forms of meaningful solutions or providing the initial population with some promising solutions. To this end, we propose three evolution approaches including modular, grammatical, and seeded evolutions for financial optimization problems. We also adopt local optimizations for fine-tuning the solutions, resulting in hybrid evolutionary algorithms. First, the thesis proposes a modular evolution. In the modular evolution, the possible forms of solutions are statically restricted to certain combinations of module solutions, which reflect more domain knowledge. To preserve the module solutions, we devise modular genetic operators which work on modular search space. The modular genetic operators and statically defined modules help genetic programming focus on highly promising search space. Second, the thesis introduces a grammatical evolution. We restrict the possible forms of solutions in genetic programming by a context-free grammar. In the grammatical evolution, genetic programming works on more extended search space than modular one. Grammatically typed genetic operators are introduced for the grammatical evolution. Compared with the modular evolution, grammatical evolution requires less domain knowledge. Finally, the thesis presents a seeded evolution. Our seeded evolution provides the initial population with partially optimized solutions. The set of genes for the partial optimization is selected in terms of encoding complexity. The partially optimized solutions help genetic algorithm find more promising solutions efficiently. Since they are not too excessively optimized, genetic algorithm is still able to search better solutions. Extensive empirical results are provided using three real-world financial optimization problems: attractive technical pattern discovery, extended attractive technical pattern discovery, and large-scale stock selection. They show that our search space reductions are fairly effective for the problems. By combining the search space reductions with systematic evolutionary algorithm frameworks, we show that evolutionary algorithms can be exploited for realistic profitable trading.1. Introduction 1 1.1 Search Methods 3 1.2 Search Space Reduction 4 1.3 Main Contributions 5 1.4 Organization 7 2. Preliminaries 8 2.1 Evolutionary Algorithms 8 2.1.1 Genetic Algorithm 10 2.1.2 Genetic Programing 11 2.2 Evolutionary Algorithms in Finance 12 2.3 Search Space Reduction 12 2.3.1 Modular Evolution 12 2.3.2 Grammatical Evolution 13 2.3.3 Seeded Evolution 14 2.3.4 Summary 14 2.4 Terminology 15 2.4.1 Technical Pattern and Technical Trading Rule 15 2.4.2 Forecasting Model and Trading Model 16 2.4.3 Portfolio and Rebalancing 17 2.4.4 Data Snooping Bias 17 2.5 Financial Optimization Problems 19 2.5.1 Attractive Technical Pattern Discovery and Its Extension 19 2.5.2 Stock Selection 20 2.6 Issues 21 2.6.1 General Assumptions 21 2.6.2 Performance Measure 22 3. Modular Evolution 23 3.1 Modular Genetic Programming 24 3.2 Hybrid Genetic Programming 28 3.3 Attractive Technical Pattern Discovery 29 3.3.1 Introduction 29 3.3.2 Problem Formulation 31 3.3.3 Modular Search Space 33 3.3.4 Experimental Results 35 3.3.5 Summary 41 4. Grammatical Evolution 44 4.1 Grammatical Type System 45 4.2 Hybrid Genetic Programming 47 4.3 Extended Attractive Technical Pattern Discovery 51 4.3.1 Introduction 51 4.3.2 Problem Formulation 54 4.3.3 Experimental Results 56 4.3.4 Summary 73 5. Seeded Evolution 76 5.1 Heuristic Seeding 77 5.2 Hybrid Genetic Algorithm 78 5.3 Large-Scale Stock Selection 81 5.3.1 Introduction 81 5.3.2 Problem Formulation 83 5.3.3 Ranking with Partitions 85 5.3.4 Experimental Results 87 5.3.5 Summary 96 6. Conclusions 104Docto

Three-dimensional cutting and packing problems and integration with vehicle routing

Orientador: Vinicius Amaral ArmentanoTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de ComputaçãoResumo: A adoção de contêineres em grande escala tornou possível o desenvolvimento do transporte multimodal. Atualmente, carregamento de caixas em contêineres é uma importante atividade em empresas que têm no transporte de carga um fator logístico de alto custo. Este trabalho apresenta o desenvolvimento e aplicação de metaheurísticas com memória adaptativa para a resolução de problemas de corte e empacotamento tridimensional, bem como a integração destes com o problema de roteamento de veículos. Mais especificamente, são tratados os problemas de carregamento de contêiner, bin packing tridimensional e roteamento de veículos capacitados com restrições de empacotamento tridimensional. Uma nova abordagem, baseada em cubóides de tamanho variável, é utilizada para calcular os padrões de carregamento tridimensional em todos os métodos propostos. Restrições de orientação, estabilidade, centro de gravidade, projeção da base de apoio e múltiplos destinos são consideradas. Extensivos testes computacionais são realizados para demonstrar o desempenho das abordagenspropostasAbstract: The wide-scale adoption of the containers made the development of the multimodal transport possible. Nowadays, shipment of boxes in containers is an important activity for companies that have in the load transport a logistic factor of high cost. This work presents the development and the application of metaheuristics with adaptive memory in order to solve three-dimensional cutting and packing problems, as well as their integration with the vehicle routing problem. In particular, problems of container loading, three-dimensional bin packing and vehicle routing with three-dimensional packing constraints are considered. Furthermore, a new approach based on maximal cuboids that fit in given empty spaces is used to calculate the packing patterns in the proposed methods. Constrains on orientation, stability, center of gravity, overhang and multiple destination are considered. Extensive computational experiments are carried out to demonstrate the performance of the proposed approachesDoutoradoAutomaçãoDoutor em Engenharia Elétric

Produktionsplanung und -steuerung in mehrstufigen Batchproduktionen : Methoden der Loskomposition und -terminierung bei stufenspezifischen Auftragsfamilien

This doctoral thesis introduces the problem of batching and scheduling non-permutation flow shops with m>=2 batch processing machines in sequence and stage specific incompatible job families. Batches are builded at each stage according to family-specific parameters. This creates a stage-interdependent batching and scheduling problem. The thesis includes the corresponding integer linear program as well as problem specific heuristics and a metaheuristic dealing with the planning problem. All methods are evaluated by real problem instances