Lori Tavasszy

Supplier selection in the airline retail industry using a funnel methodology: Conjunctive screening method and fuzzy AHP

Abstract Since a company can only perform as well as it is allowed to by its suppliers, the importance of supplier selection in supply chain management has been increasingly recognized. Supplier selection can best be described as a highly complex process, due to the involvement of many, sometimes conflicting, qualitative and quantitative criteria. The objective is to select the most suitable supplier(s) that meet a company’s specific needs. This paper investigates supplier selection in the airline retail industry. We discuss a number of issues that make airline retail complex and distinguish it from conventional retail. The supplier selection problem is solved by means of a two-phased methodology. In the first phase, a conjunctive screening method is used, which aims to reduce the initial set of potential suppliers prior to the comprehensive final choice phase. In the second phase, a fuzzy analytic hierarchy process (AHP) is used, in which suppliers are evaluated against the main criteria and sub-criteria. By combining the decision-maker’s preferences, using the developed methodology will eventually result in a ranking of suppliers that makes it possible to select the most suitable supplier(s). The proposed methodology is applied to one of the largest airlines in Europe, the Royal Dutch Airlines (KLM), and the results are discussed extensively in this paper. We conclude by proposing avenues for future research regarding the general applicability and further extensions.

GenCLOn: An ontology for city logistics

City logistics is a discipline specialized to cope with the sustainability problems encountered in urban freight transport. A key characteristic of it is the heterogeneity of the stakeholders involved. Besides the traditional logistics actors such as shippers, carriers and receivers that share consistent interests (i.e. price and quality), city logistics highly respect the interests of public administrators and citizens that care more about the social welfare. To reach an optimal balance between private and public benefit, it is necessary to understand and in turn forecast the behavior pattern of different groups. In recent years, agent-based modeling has been practiced as an unconventional tool to fulfill this task for its strong capability on capturing the dynamic behavior of individual stakeholders and their interconnections. Referring to other domains (e.g. energy system) where the application of agent-based modeling is relatively mature, a following urgency is to achieve interoperability and in turn reusability between models via introducing formal ontology as a shared template with which developers can standardize their models. This paper introduces an initiative of developing an ontology that formalizes the domain knowledge of city logistics.

Customized Solutions for Sustainable City Logistics: The Viability of Urban Freight Consolidation Centres

The current way of organizing the urban freight transport system is inefficient and generates an unsound basis for sustainable development. Urban freight transport is widely recognized for its unsustainable impacts on the environment. The common perception is that the current urban freight transport system has negative impacts on all three sustainability P’s: people, profit and planet, also known as the social, economic and environmental issues of sustainability.

Relevance of City Logistics Modelling Efforts: A Review

Abstract This paper presents a review of city logistics (also known as urban freight transportation) modelling efforts reported in the literature for urban freight analysis. The review is based on an extensive search of the academic literature. We position the contributions in a framework that takes into account the diversity and complexity found in the present-day city logistics practice. The framework covers the fundamental aspects in the modelling selection process, including: (1) the stakeholders involved in the model, (2) the defining criteria, that is the descriptor for modelling purpose, (3) the objective of the model and (4) the solution approach implemented for achieving the objective. In our discussion and overview, we take these situational factors as the starting point for categorizing and evaluating the city logistics modelling literature. The review analyses the trends of city logistics modelling research in terms of its relevance to city logistics problems and attempts to identify missing links in modelling the urban freight domain.

Ontology-based multi-agent system for urban freight transportation

Congestion, pollution, and safety are some of the most worrisome side-effects of the urban goods movement activities. These problems are generally attributed to the underlying characteristics of the domain such as heterogeneous stakeholders, their conflicting objectives and resulting distributed decision-making. Such autonomous decision-making stakeholders do not efficiently cooperate and coordinate while performing city logistics activities. The ensuing inefficient use of resources (e.g. goods delivery vehicle, time, etc.) gives rise to the above-mentioned problems. To reduce the negative externalities of urban goods movement, we first must understand the decision-making process of the city logistics stakeholder under different situations. Agent-based simulation modelling technique is such an approach where distributed decision-making of the multiple stakeholders can be included by modelling each entity as an autonomous agent. In this paper, we propose the use of a knowledge data model of urban freight domain – city logistics ontology – to develop an agent-based model. City logistics ontology is a knowledge model which includes city logistics entities (e.g. stakeholders, resources, etc.) and relationships between them in a structured form. The paper focuses on the usefulness of ontology in the development of agent-based model for city logistics domain, and attempts to demonstrate the effectiveness of agent technology in analysing the urban freight decision-making processes.

A multi-objective model for lot-sizing with supplier selection for an assembly system

Lot-sizing with supplier selection (LS-SS) is a fast-growing offspring of two major problem parents in logistics and supply chain management (‘lot-sizing’ and ‘supplier selection’). The model proposed in this paper is an attempt to extend it to an assembly system, by formulating a multi-objective model for an integrative problem of LS-SS for assembly items. The total costs of the system, consisting of purchasing, ordering, transportation, assembly, and holding, is considered the first objective function, while the total reliability of the finished products is considered the second objective function. The decision-maker aims to minimise the total costs while maximising the total reliability. Several constraints of the system (e.g. storage capacity, supplier production capacity) are taken into account. Given the complexity of the model, a heuristic evolutionary algorithm is proposed to solve the model. The results indicate which assembly items to order in which quantities, from which suppliers and in which time periods.

Mega-projects in intermodal freight transport: innovation adoption

This comprehensive and accessible Handbook presents state-of-the-art research on the decision-making processes in the deliverance of mega-projects – large infrastructure projects for the transportation of people and/or goods.

An empirical agent-based simulation system for urban goods transport (MASS-GT)

Abstract Urban planners face a few challenges in making urban freight transport more sustainable: reduce urban congestion, provide reliable delivery windows, decrease logistic costs, reduce emissions, improve safety. New data may provide a key in tackling these issues. This paper presents an agent-based urban freight modeling framework: MASS-GT. Objective of the project is to develop a comprehensive simulation framework that describes logistic decision making in the context of urban transport planning. Empirical basis is provided by a large dataset with observed freight transport data for The Netherlands. Part of the data has been collected using an automated procedure to report complete freight trip patterns from the transport management system. This provides more dense and complete data compared to conventional internet surveys. The paper describes the design principles for agents, markets and logistic decisions. Furthermore we elaborate on the incremental development path of building a comprehensive agent-based simulation system. We describe the first baseline prototype of the agent based modeling framework that simulates all urban freight transport patterns for an urban area, in the case the agglomeration of Rotterdam. This baseline model applies a data driven simulation approach; future work will consists of further improving this framework with the implementation of discrete choice models for logistic decisions.