Rough-Cut Capacity Planning in Multimodal Freight Transportation Networks

A main challenge in transporting cargo for United States Transportation Command (USTRANSCOM) is in mode selection or integration. Demand for cargo is time sensitive and must be fulfilled by an established due date. Since these due dates are often inflexible, commercial carriers are used at an enormous expense, in order to fill the gap in organic transportation asset capacity. This dissertation develops a new methodology for transportation capacity assignment to routes based on the Resource Constrained Shortest Path Problem (RCSP). Routes can be single or multimodal depending on the characteristics of the network, delivery timeline, modal capacities, and costs. The difficulty of the RCSP requires use of metaheuristics to produce solutions. An Ant Colony System to solve the RCSP is developed in this dissertation. Finally, a method for generating near Pareto optimal solutions with respect to the objectives of cost and time is developed

Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

Collaboration in urban distribution of online grocery orders

Purpose: Population growth, urbanisation and the increased use of online shopping are some of the key challenges affecting the traditional logistics model. The purpose of this paper is to focus on the distribution of grocery products ordered online and the subsequent home delivery and click and collect services offered by online retailers to fulfil these orders. These services are unsustainable due to increased operational costs, carbon emissions, traffic and noise. The main objective of the research is to propose sustainable logistics models to reduce economic, environmental and social costs whilst maintaining service levels. Design/methodology/approach: The authors have a mixed methodology based on simulation and mathematical modelling to evaluate the proposed shared logistics model using: primary data from a major UK retailer, secondary data from online retailers and primary data from a consumer survey on preferences for receiving groceries purchased online. Integration of these three data sets serves as input to vehicle routing models that reveal the benefits from collaboration by solving individual distribution problems of two retailers first, followed by the joint distribution problem under single decision maker assumption. Findings: The benefits from collaboration could be more than 10 per cent in the distance travelled and 16 per cent in the time required to deliver the orders when two online grocery retailers collaborate in distribution activities. Originality/value: The collaborative model developed for the online grocery market incentivises retailers to switch from current unsustainable logistics models to the proposed collaborative models

The design of effective and robust supply chain networks

Tableau d’honneur de la Faculté des études supérieures et postdoctorales, 2009-2010Pour faire face aux risques associés aux aléas des opérations normales et aux périls qui menacent les ressources d'un réseau logistique, une méthodologie générique pour le design de réseaux logistiques efficaces et robustes en univers incertain est développée dans cette thèse. Cette méthodologie a pour objectif de proposer une structure de réseau qui assure, de façon durable, la création de valeur pour l'entreprise pour faire face aux aléas et se prémunir contre les risques de ruptures catastrophiques. La méthodologie s'appuie sur le cadre de prise de décision distribué de Schneeweiss et l'approche de modélisation mathématique qui y est associée intègre des éléments de programmation stochastique, d'analyse de risque et de programmation robuste. Trois types d'événements sont définis pour caractériser l'environnement des réseaux logistiques: des événements aléatoires (ex. la demande, les coûts et les taux de changes), des événements hasardeux (ex. les grèves, les discontinuités d'approvisionnement des fournisseurs et les catastrophes naturelles) et des événements profondément incertains (ex. les actes de sabotage, les attentats et les instabilités politiques). La méthodologie considère que l'environnement futur de l'entreprise est anticipé à l'aide de scénarios, générés partiellement par une méthode Monte-Carlo. Cette méthode fait partie de l'approche de solution et permet de générer des replications d'échantillons de petites tailles et de grands échantillons. Elle aide aussi à tenir compte de l'attitude au risque du décideur. L'approche générique de solution du modèle s'appuie sur ces échantillons de scénarios pour générer des designs alternatifs et sur une approche multicritère pour l'évaluation de ces designs. Afin de valider les concepts méthodologiques introduits dans cette thèse, le problème hiérarchique de localisation d'entrepôts et de transport est modélisé comme un programme stochastique avec recours. Premièrement, un modèle incluant une demande aléatoire est utilisé pour valider en partie la modélisation mathématique du problème et étudier, à travers plusieurs anticipations approximatives, la solvabilité du modèle de design. Une approche de solution heuristique est proposée pour ce modèle afin de résoudre des problèmes de taille réelle. Deuxièmement, un modèle incluant les aléas et les périls est utilisé pour valider l'analyse de risque, les stratégies de resilience et l'approche de solution générique. Plusieurs construits mathématiques sont ajoutés au modèle de base afin de refléter différentes stratégies de resilience et proposer un modèle de décision sous risque incluant l'attitude du décideur face aux événements extrêmes. Les nombreuses expérimentations effectuées, avec les données d'un cas réaliste, nous ont permis de tester les concepts proposés dans cette thèse et d'élaborer une méthode de réduction de complexité pour le modèle générique de design sans compromettre la qualité des solutions associées. Les résultats obtenus par ces expérimentations ont pu confirmer la supériorité des designs obtenus en appliquant la méthodologie proposée en termes d'efficacité et de robustesse par rapport à des solutions produites par des approches déterministes ou des modèles simplifiés proposés dans la littérature

Storage Business Models: Lessons for Electricity from Natural Gas, Cloud Data and Frozen Food

The aim of this paper is to evaluate different well-established non-electrical storage markets (gas, frozen food and cloud storage) in order to identify relevant lessons for electrical energy storage (EES) connected to the electricity distribution networks. The case studies that have been evaluated are Centrica Storage (gas storage), Google Drive (cloud storage) and Oakland International (frozen food storage). A specific business model methodology has been selected for comparing the different business model components across these sectors. The methodology (following Johnson et al., 2008) refers to key interconnected components: customer value proposition, the revenue formula, key resources and key processes. The evaluation of the three case studies suggests that well-developed business models already exist in growing and mature storage markets. Regulation also plays an important role across the different storage markets and business model components, how-ever its importance varies depending on the type of market. Innovation in storage business models is also observed (technological and contractual) which should be also facilitated in EES. Innovation helps move markets towards more sustainable business models

A Hybrid MCDM Approach to Transshipment Port Selection

Port selection is an intrinsic supply-chain problem that has substantial impact on development of local economies. Shipping business environment developed into complex system where decision making is derived from uncertain and incomplete data. In this study we present a conceptual integrated Multi-Criteria Decision solution to transshipment port selection problem based on Best-Worst MCDM and Artificial Bee Colony Algorithm. Through literature review and expert analysis, 50 relevant criteria have been identified as relevant to the transshipment port selection problem. Decision makers within liner shipping companies evaluate transshipment port selection criteria and establish ranking that is used to determine crisp solution with lowest consistency ratio. ABC based algorithm is used to reduce computational complexity and deliver a single optimal solution by solving both objective and constraint violation functions

Importance and value of airline service attributes. Routes from Helsinki to Germany in non-business segments

This study focuses on analyzing importance of airline service attributes on routes between Helsinki-Vantaa Airport and Germany. The goal of the study is to find out which airline service attributes are important for the passengers and are there differences in the importance levels caused by the type of passenger. Another interest area was willingness-to-pay measures for two airline service attributes and possible differences inside the focus group. Literature review discusses the most relevant theoretical areas and earlier research in the area of passengers’ airline choice process. Empirical part of the study was conducted as quantitative research. Respondents were recruited at Helsinki-Vantaa Airport and three forums to take part in the questionnaire built with Sawtooth Software to dedicated web domain. Altogether 166 completed and applicable responses were received for the analysis. Willingness-to-pay measures are calculated for reduced travel time and food service attribute from individual-level utilities, which were estimated with hierarchical Bayes estimation. The two most essential findings are the importance levels of different service attributes and willingness-to-pay measures. Low price of the ticket, direct flight to the destination in addition to safety reputation of the airline and punctuality of the flight were found as being the most important attributes. Frequent-flyer programs, name of the airline and seat width were found to be the least important attributes. Some demographic and traveler specific variables were found to affect the importance levels. Average willingness-to-pay measures for direct flight with the reduction of flight with two hours was 97,94 euros and willingness-to-pay for free food and drinks 19,55 Eur. Cluster analysis revealed three clusters; time sensitive (62,65% of the respondents), price sensitive (22,30%), and time sensitive, conditional buyers (15,05%)

Applications of advanced transport aircraft in developing countries

Four representative market scenarios were studied to evaluate the relative performance of air-and surface-based transportation systems in meeting the needs of two developing contries, Brazil and Indonesia, which were selected for detailed case studies. The market scenarios were: remote mining, low-density transport, tropical forestry, and large cargo aircraft serving processing centers in resource-rich, remote areas. The long-term potential of various aircraft types, together with fleet requirements and necessary technology advances, is determined for each application

The co-incident flow of work pieces and cutting tools in a restricted category of flexible machining cells

The work reported in this thesis describes research carried out into the detailed design and operation of Flexible Machining Cells (FMC) incorporating automated work and tool flow, dual flow. Three modes of cell management are considered for dual flow cells, where the author examines both their operational and economic performance. A framework is defined for investigating these dual flow cells, and a structured approach providing a novel and detailed modelling capability is described. The question of how this approach compares to single flow modelling and the additional or alternative requirements for dual flow modelling is examined via the following key areas; the specification of material handling requirements, tool transportation and issue and finally, the control required to examine the interaction between the two flows operating concurrently. The framework is tested for its industrial applicability via an industrial case study. A major aim of this study is to examine the view that a hybrid cell management strategy, competitive management, could outperform the other strategies examined. The aim of this methodology is to provide a solution for the control of FMCs. Emphasis is placed on the ease of control and how the loading and control rules selection can maximise economic enhancement of a cells performance