Optimising and recognising 2-stage delivery chains with time windows

In logistic delivery chains time windows are common. An arrival has to be in a certain time interval, at the expense of waiting time or penalties if the time limits are exceeded. This paper looks at the optimal placement of those time intervals in a specific case of a barge visiting two ports in sequence. For the second port a possible delay or penalty should be incorporated. Next, recognising these penalty structures in data is analysed to if see certain patterns in public travel data indicate that a certain dependency exists

Assessment of local food distribution

There is increasing interest in local food, as consumers feel confidence in such food. Local food has good opportunities to fulfil quality aspects/requirements of transparency and traceability in the supply chain due to the possibilities for direct interaction between producers and consumers. However, local food producers often face logistics challenges due to their small scale, decentralisation and integration difficulties with larger supply chains. This necessitates analysis of specific logistics systems in order to identify successful approaches for improving the local food supply chain. Important questions are whether local and small-scale food producers can transport their goods more efficiently and how they can improve distribution and its environmental impact. This thesis examined local food distribution systems to determine how cooperation, optimisation and integration in the supply chain can make the distribution systems of local and small-scale food producers more efficient and to estimate the environmental impact of the transport. The work comprised a producer survey examining marketing channels and impediments to development in local supply chains in Sweden, three case studies on distribution systems of different scales and an analysis of the environmental impact of local food distribution, based on quantification of emissions and energy use. The case studies involved small-scale producers integrating their marketing and distribution into a large retail chain using an electronic trading system; the distribution of local food in and around a city; and a distribution system for municipal units in four municipalities. Based on the results, distribution strategies for local and small-scale food producers and distributors were developed and refined. By mapping distribution systems and impediments to development, optimising routes and estimating emissions, potential improvements in the distribution system were identified. This revealed scope for local and small-scale food producers to improve their distribution and reduce their environmental impact. Cooperation, integration and route optimisation are suitable strategies for producers to adopt in order to make their transport more efficient

Assessing the feasibility of archetypal transition pathways towards carbon neutrality – A comparative analysis of European industries

Analyses of the future for manufacturing and heavy industries in a climate constrained world many times focus on technological innovations in the early stages of the value chain, assuming few significant changes are plausible, wanted, or necessary throughout the rest of the value chain. Complex questions about competing interests, different ways of organising resource management, production, consumption, and integrating value chains are thus closed down to ones about efficiencies, pay-back times, and primary processing technologies. In this analysis, we move beyond this to identify archetypal pathways that span across value chains in four emissions intensive industries: plastics, steel, pulp and paper, and meat and dairy. The pathways as presented in the present paper were inductively identified in a multi-stage process throughout a four-year European research project. The identified archetypal pathways are i) production and end-use optimisation, ii) electrification with CCU, iii) CCS, iv) circular material flows, and v) diversification of bio-feedstock use. The pathways are at different stages of maturity and furthermore their maturity vary across sectors. The pathways show that decarbonisation is likely to force value chains to cross over traditional boundaries. This implies that an integrated industrial and climate policy must handle both sectoral specificities and commonalities for decarbonised industrial development.publishedVersio

A survey of AI in operations management from 2005 to 2009

Purpose: the use of AI for operations management, with its ability to evolve solutions, handle uncertainty and perform optimisation continues to be a major field of research. The growing body of publications over the last two decades means that it can be difficult to keep track of what has been done previously, what has worked, and what really needs to be addressed. Hence this paper presents a survey of the use of AI in operations management aimed at presenting the key research themes, trends and directions of research. Design/methodology/approach: the paper builds upon our previous survey of this field which was carried out for the ten-year period 1995-2004. Like the previous survey, it uses Elsevier’s Science Direct database as a source. The framework and methodology adopted for the survey is kept as similar as possible to enable continuity and comparison of trends. Thus, the application categories adopted are: design; scheduling; process planning and control; and quality, maintenance and fault diagnosis. Research on utilising neural networks, case-based reasoning (CBR), fuzzy logic (FL), knowledge-Based systems (KBS), data mining, and hybrid AI in the four application areas are identified. Findings: the survey categorises over 1,400 papers, identifying the uses of AI in the four categories of operations management and concludes with an analysis of the trends, gaps and directions for future research. The findings include: the trends for design and scheduling show a dramatic increase in the use of genetic algorithms since 2003 that reflect recognition of their success in these areas; there is a significant decline in research on use of KBS, reflecting their transition into practice; there is an increasing trend in the use of FL in quality, maintenance and fault diagnosis; and there are surprising gaps in the use of CBR and hybrid methods in operations management that offer opportunities for future research. Design/methodology/approach: the paper builds upon our previous survey of this field which was carried out for the 10 year period 1995 to 2004 (Kobbacy et al. 2007). Like the previous survey, it uses the Elsevier’s ScienceDirect database as a source. The framework and methodology adopted for the survey is kept as similar as possible to enable continuity and comparison of trends. Thus the application categories adopted are: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Research on utilising neural networks, case based reasoning, fuzzy logic, knowledge based systems, data mining, and hybrid AI in the four application areas are identified. Findings: The survey categorises over 1400 papers, identifying the uses of AI in the four categories of operations management and concludes with an analysis of the trends, gaps and directions for future research. The findings include: (a) The trends for Design and Scheduling show a dramatic increase in the use of GAs since 2003-04 that reflect recognition of their success in these areas, (b) A significant decline in research on use of KBS, reflecting their transition into practice, (c) an increasing trend in the use of fuzzy logic in Quality, Maintenance and Fault Diagnosis, (d) surprising gaps in the use of CBR and hybrid methods in operations management that offer opportunities for future research. Originality/value: This is the largest and most comprehensive study to classify research on the use of AI in operations management to date. The survey and trends identified provide a useful reference point and directions for future research

Framework of synchromodal transportation problems

Though literature reviews of synchromodal transportation exist, no generalised mathematical model of these problems has been found yet. In this paper such a framework is introduced, by which mathematical models described in literature on synchromodal transportation problems can be classified. This framework should help researchers and developers to find solution methodologies that are commonly used in their problem instance and to grasp characteristics of the models and cases in a compact way, enabling easy classification, comparison and insight in complexity

Network FOuNTAIN a CDBB network: For ONTologies and information maNagement in digital built Britain. Final report.

Network FOuNTAIN is the Network For ONTologies And Information maNagement in Digital Built Britain. The Network is supported by the Centre for Digital Built Britain. The vision of the Network is for all stakeholders in Digital Built Britain (DBB) to be able to meet their information needs. With the establishment of concepts such as Building Information Modelling (BIM) and Common Data Environments (CDE), built environment design, construction and operation are becoming increasingly information-intensive. The Network undertook five workshop activities between July and December 2018. This report summarises the proceedings of these workshops, and in particular establishes future capabilities needed to realise the vision of DBB

Supply chain business modelling

The developed work is motivated by the hypothesis that the presented Supply Chain Business Model is a practical and comprehensive approach to support not only operational day-to-day business decisions, but most importantly strategic and long term decisions that may define the success and the longevity of a business. Conceptually, the Business Supply Chain Model developed in this thesis replicates the behaviour and decision making of the different agents in a supply chain, and an Optimisation Module determines the optimised parameters that maximise the overall business profit, whatever scenario it may be. In the optimisation module, a Genetic Algorithm was used to determine the best equation parameters for each individual agent that optimise the overall supply chain profit. Furthermore, several business case-scenarios are presented and the findings highlighted. These case-scenarios prove that: the HC model is robust when subjected to predictable or unpredictable causes of variability; the bullwhip effect can be reduced significantly by applying GA as the optimisation tool; the improvement of profits needs to be evaluated at a global scale, independently of the individual agents’ profit; impact of supply shortages in the SC ; retail expansion analysis; delivery patterns change impact in profitability; impact of sourcing decisions in the SC profitability; model suitability for seasonal vs. non-seasonal products. The SC Modelling framework generic and globalising approach means that is easily applied and transposed to any other business realities and it can be easily changed to reflect other SC scenarios. The costing model associated means that, at any point in the network, all costs and profits can be easily measured. For the first time the shelf-life of a product captured and losses of product due to BBE dates, quantified. In this model the optimisation methodology runs parallel to the developed simulation tool, so the optimisation should be only run for new scenarios