A viral system to optimise the daily drayage problem

The intermodal transport chain can become more efficient by means of a good organisation of the drayage movements. Drayage in intermodal container terminals involves the pick up or delivery of containers at customer locations, and the main objective is normally the assignment of transportation tasks to the different vehicles, often with the presence of time windows. This paper focuses on a new approach to tackle the daily drayage problem by the use of viral system (VS). VS is a novel bio-inspired approach that makes use of a virus-infection biological analogy that is producing very satisfactory results when dealing with complex problems with huge feasibility region.Unión Europea TEC2013-47286-C3-3-

Planning and Scheduling Optimization

Although planning and scheduling optimization have been explored in the literature for many years now, it still remains a hot topic in the current scientific research. The changing market trends, globalization, technical and technological progress, and sustainability considerations make it necessary to deal with new optimization challenges in modern manufacturing, engineering, and healthcare systems. This book provides an overview of the recent advances in different areas connected with operations research models and other applications of intelligent computing techniques used for planning and scheduling optimization. The wide range of theoretical and practical research findings reported in this book confirms that the planning and scheduling problem is a complex issue that is present in different industrial sectors and organizations and opens promising and dynamic perspectives of research and development

Historia, evolución y perspectivas de futuro en la utilización de técnicas de simulación en la gestión portuaria: aplicaciones en el análisis de operaciones, estrategia y planificación portuaria

Programa Oficial de Doutoramento en Análise Económica e Estratexia Empresarial. 5033V0[Resumen] Las técnicas de simulación, tal y como hoy las conocemos, comenzaron a mediados del siglo XX; primero con la aparición del primer computador y el desarrollo del método Monte Carlo, y más tarde con el desarrollo del primer simulador de propósito específico conocido como GPS y desarrollado por Geoffrey Gordon en IBM y la publicación del primer texto completo dedicado a esta materia y llamado the Art of Simulation (K.D. Tocher, 1963). Estás técnicas han evolucionado de una manera extraordinaria y hoy en día están plenamente implementadas en diversos campos de actividad. Las instalaciones portuarias no han escapado de esta tendencia, especialmente las dedicadas al tráfico de contenedores. Efectivamente, las características intrínsecas de este sector económico, le hacen un candidato idóneo para la implementación de modelos de simulación con propósitos y alcances muy diversos. No existe, sin embargo y hasta lo que conocemos, un trabajo científico que compile y analice pormenorizadamente tanto la historia como la evolución de simulación en ambientes portuarios, ayudando a clasificar los mismos y determinar cómo estos pueden ayudar en el análisis económico de estas instalaciones y en la formulación de las oportunas estrategias empresariales. Este es el objetivo último de la presente tesis doctoral.[Resumo] As técnicas de simulación, tal e como hoxe as coñecemos, comezaron a mediados do século XX; primeiro coa aparición do computador e o desenvolvemento do método Monte Carlo e máis tarde co desenvolvemento do primeiro simulador de propósito específico coñecido como GPS e desenvolvido por Geoffrey Gordon en IBM e a publicación do primeiro texto completo dedicado a este tema chamado “A Arte da Simulación” (K.D. Tocher, 1963). Estas técnicas evolucionaron dun xeito extraordinario e hoxe en día están plenamente implementadas en diversos campos de actividade. As instalacións portuarias non escaparon desta tendencia, especialmente as dedicadas ao tráfico de contenedores. Efectivamente, as características intrínsecas deste sector económico, fanlle un candidato idóneo para a implementación de modelos de simulación con propósitos e alcances moi variados. Con todo, e ata o que coñecemos, non existe un traballo científico que compila e analiza de forma detallada tanto a historia como a evolución da simulación en estes ambientes portuarios, clasificando os mesmos e determinando como estes poden axudar na análise económica destas instalacións e na formulación das oportunas estratexias empresariais. Este é o último obxectivo da presente tese doutoral.[Abstract] Simulation, to the extend that we understand it nowadays, began in the middle of the 20th century; first with the appearance of the computer and the development of the Monte Carlo method, and later with the development of the first specific purpose simulator known as GPS developed by Geoffrey Gordon in IBM. This author published the first full text devoted to this subject “The Art of Simulation” in 1963. These techniques have evolved in an extraordinary way and nowadays they are fully implemented in different fields of activity. Port facilities have not escaped this trend, especially those dedicated to container traffic. Indeed, the intrinsic characteristics of this economic sector, make it a suitable candidate for the implementation of simulation with very different purposes and scope. However, to the best of our knowelegde, there is not a scientific work that compiles and analyzes in detail both, the history and the evolution of simulation in port environments, contributing to classify them and determine how they can help in the economic analysis of these facilities and in the formulation of different business strategies. This is the ultimate goal of this doctoral thesis

Evolutionary Computation

This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. This book also presents new algorithms based on several analogies and metafores, where one of them is based on philosophy, specifically on the philosophy of praxis and dialectics. In this book it is also presented interesting applications on bioinformatics, specially the use of particle swarms to discover gene expression patterns in DNA microarrays. Therefore, this book features representative work on the field of evolutionary computation and applied sciences. The intended audience is graduate, undergraduate, researchers, and anyone who wishes to become familiar with the latest research work on this field

Holistic, data-driven, service and supply chain optimisation: linked optimisation.

The intensity of competition and technological advancements in the business environment has made companies collaborate and cooperate together as a means of survival. This creates a chain of companies and business components with unified business objectives. However, managing the decision-making process (like scheduling, ordering, delivering and allocating) at the various business components and maintaining a holistic objective is a huge business challenge, as these operations are complex and dynamic. This is because the overall chain of business processes is widely distributed across all the supply chain participants; therefore, no individual collaborator has a complete overview of the processes. Increasingly, such decisions are automated and are strongly supported by optimisation algorithms - manufacturing optimisation, B2B ordering, financial trading, transportation scheduling and allocation. However, most of these algorithms do not incorporate the complexity associated with interacting decision-making systems like supply chains. It is well-known that decisions made at one point in supply chains can have significant consequences that ripple through linked production and transportation systems. Recently, global shocks to supply chains (COVID-19, climate change, blockage of the Suez Canal) have demonstrated the importance of these interdependencies, and the need to create supply chains that are more resilient and have significantly reduced impact on the environment. Such interacting decision-making systems need to be considered through an optimisation process. However, the interactions between such decision-making systems are not modelled. We therefore believe that modelling such interactions is an opportunity to provide computational extensions to current optimisation paradigms. This research study aims to develop a general framework for formulating and solving holistic, data-driven optimisation problems in service and supply chains. This research achieved this aim and contributes to scholarship by firstly considering the complexities of supply chain problems from a linked problem perspective. This leads to developing a formalism for characterising linked optimisation problems as a model for supply chains. Secondly, the research adopts a method for creating a linked optimisation problem benchmark by linking existing classical benchmark sets. This involves using a mix of classical optimisation problems, typically relating to supply chain decision problems, to describe different modes of linkages in linked optimisation problems. Thirdly, several techniques for linking supply chain fragmented data have been proposed in the literature to identify data relationships. Therefore, this thesis explores some of these techniques and combines them in specific ways to improve the data discovery process. Lastly, many state-of-the-art algorithms have been explored in the literature and these algorithms have been used to tackle problems relating to supply chain problems. This research therefore investigates the resilient state-of-the-art optimisation algorithms presented in the literature, and then designs suitable algorithmic approaches inspired by the existing algorithms and the nature of problem linkages to address different problem linkages in supply chains. Considering research findings and future perspectives, the study demonstrates the suitability of algorithms to different linked structures involving two sub-problems, which suggests further investigations on issues like the suitability of algorithms on more complex structures, benchmark methodologies, holistic goals and evaluation, processmining, game theory and dependency analysis

An overview of fuzzy techniques in supply chain management: bibliometrics, methodologies, applications and future directions

Every practice in supply chain management (SCM) requires decision making. However, due to the complexity of evaluated objects and the cognitive limitations of individuals, the decision information given by experts is often fuzzy, which may make it difficult to make decisions. In this regard, many scholars applied fuzzy techniques to solve decision making problems in SCM. Although there were review papers about either fuzzy methods or SCM, most of them did not use bibliometrics methods or did not consider fuzzy sets theory-based techniques comprehensively in SCM. In this paper, for the purpose of analyzing the advances of fuzzy techniques in SCM, we review 301 relevant papers from 1998 to 2020. By the analyses in terms of bibliometrics, methodologies and applications, publication trends, popular methods such as fuzzy MCDM methods, and hot applications such as supplier selection, are found. Finally, we propose future directions regarding fuzzy techniques in SCM. It is hoped that this paper would be helpful for scholars and practitioners in the field of fuzzy decision making and SCM

遺伝的アルゴリズムの改良に基づくマルチターゲットの運輸問題に関する研究

With the rapid development of economic globalization and information technology, rapid changes have taken place in all fields of society. The status of modern logistics industry in the process of the flow of social means of production and commodities has become increasingly prominent, accompanied by profound changes in production and manufacturing, material circulation, commodity transactions and management methods. Logistics cost accounts for a large share of national GDP, which can reflect the quality and scale of a country\u27s national economy, reduce the logistics cost of enterprises, and greatly improve the profit space. Especially under the background of economic globalization, the competition among enterprises is increasingly fierce, and the impact of logistics on the competitiveness of enterprises is increasingly obvious. In the modern e-commerce environment, with the rapid development of science and technology, the space for enterprises to obtain profits from the products themselves has been greatly reduced. In order to reduce costs and improve profits as much as possible, enterprises focus on logistics. In the whole logistics system, transportation is a very important link. Therefore, efforts to reduce the cost of logistics and transportation can greatly reduce the cost of the entire logistics system. This paper starts from the main factors involved in the transportation logistics, optimizes the main factors affecting the logistics, reduces costs and improves profits.Firstly, this paper discusses and studies the distribution personnel, mainly including the logistics distribution under the limitation of personnel fatigue and the delivery distribution mode under the new mode of personnel allocation - "crowdsourcing logistics". Aiming at the research on the limitation of fatigue, aiming at the maximization of customer satisfaction and the minimization of total cost, this paper constructs a model of path optimization for driver\u27s fatigue driving, and designs a single Partheno-genetic algorithm for the model, which is verified by the distribution case of Japan\u27s otaku. On the research of crowdsourcing delivery, taking the delivery network as the research object, this paper analyzes the distribution process, mode and existing problems of crowdsourcing delivery mode. Based on the purpose of optimizing the distribution network, taking the shortest distribution path and the least time delay as the objective function, the basic optimization model and dynamic optimization model of crowdsourcing distribution path with time window are established, and the rationality of the model is evaluated.Secondly, from the perspective of vehicle research and analysis, mainly study the two-tier node logistics distribution mode based on heterogeneous vehicles. This paper analyzes the common transportation vehicle selection problem in the existing transportation. Based on the genetic algorithm, taking the transportation cost of the double-layer logistics node of a city\u27s seafood products as the optimization goal, and comprehensively considering the problem of taking delivery vehicle route and vehicle configuration strategy of different routes at the same time, the mathematical model of vehicle scheduling and transportation route problem in the double-layer node transportation route is established. In this paper, MATLAB software is used to solve the model based on traditional genetic algorithm and Partheno-genetic algorithm, and the correctness and effectiveness of the model and Partheno-genetic algorithm are verified.Then, from the perspective of transportation path mode, the research mainly involves the current hot "multimodal transport" problem. In this paper, the coal transportation in a country is taken as the research object. Under the mode of "iron water combined transportation", how to reasonably distribute the transportation capacity and correctly select the transportation mode can realize the enterprise to control the logistics cost and ensure the maximum profit. At the same time, based on the traditional genetic algorithm mechanism, aiming at the premature and local search ability of the traditional genetic algorithm in solving the logistics transportation path optimization problem are analyzed Due to the shortage of power, a hybrid genetic algorithm is proposed to solve the model.Finally, the optimization algorithm of logistics distribution is discussed. This paper presents a hybrid genetic algorithm based on information entropy and game theory. First, the initial population is generated by calculating population diversity with information entropy. Combined with parallel genetic algorithm, standard genetic algorithm (SGA), Partheno-genetic algorithm (PGA) and hybrid genetic algorithm (sga-pga) which integrates standard genetic algorithm and Partheno-genetic algorithm (sga-pga) are used to perform evolutionary operations. At the parallel node, information entropy and fitness value of each sub population are used Finally, three programs checking functions Rosenbrock function, Rastrigin function and Schaffer function are introduced to analyze the performance superiority of the algorithm.博士(工学)法政大学 (Hosei University