Ron van Duin

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.

Improving Inventory Management Performance Using a Process-Oriented Measurement Framework

Enterprise Resource Planning systems have been introduced to support the efficient and effective execution of business processes. In practice, this may not fully succeed. This also holds for inventory management (IM), part of the sub-field within logistics termed supply chain management. By analyzing the IM business process, eleven potential benefits are indicated. Next, by using a Business Intelligence approach, key performance indicators (KPIs) are selected to measure the performance of sub-processes. Putting this together yields an IM framework that is used to obtain a generic, coherent picture of IM processes in different organizations. The proposed framework is tested using experts’ opinions and two case studies. The experts’ comments yielded a list of top-10 KPIs. The case study results show that some of the potential benefits are also observed in practice. Future research may reveal that comparable performance improvements are possible in other ERP domains based on similar measurement frameworks.