Dagstuhl Reports : Volume 1, Issue 2, February 2011

Online Privacy: Towards Informational Self-Determination on the Internet (Dagstuhl Perspectives Workshop 11061) : Simone Fischer-Hübner, Chris Hoofnagle, Kai Rannenberg, Michael Waidner, Ioannis Krontiris and Michael Marhöfer Self-Repairing Programs (Dagstuhl Seminar 11062) : Mauro Pezzé, Martin C. Rinard, Westley Weimer and Andreas Zeller Theory and Applications of Graph Searching Problems (Dagstuhl Seminar 11071) : Fedor V. Fomin, Pierre Fraigniaud, Stephan Kreutzer and Dimitrios M. Thilikos Combinatorial and Algorithmic Aspects of Sequence Processing (Dagstuhl Seminar 11081) : Maxime Crochemore, Lila Kari, Mehryar Mohri and Dirk Nowotka Packing and Scheduling Algorithms for Information and Communication Services (Dagstuhl Seminar 11091) Klaus Jansen, Claire Mathieu, Hadas Shachnai and Neal E. Youn

A Relocation Diffusion Model of Selected Retail Businesses in Hamilton, Ontario

In Hamilton, Ontario from 1969 to 1973 the Civic Square Urban Renewal Project was carried out in part of the Central Business District. As a result most of the businesses in the project area were forced to move. This thesis examines the relocation decision which was made by the entrepreneurs who operated retail businesses in the Civic Square Area. The factors which were considered important as input in their decision were incorporated into a model which projects a relocation diffusion pattern similar to the actual pattern created when these businesses spread to other sections of the C.B.D. The likelihood of the retailer choosing to relocate on a particular block within the C.B.D. is related to a number of factors which are combined in the model. These include the number of store sites in a block, the frequency of vacant stores that occur in the area and the distance of the new site from the original location in the C.B.D. However, not all businesses were prepared to compete for the most desirable locations. Those firms which had not been paying a low rent or were less successful were not likely to outbid a firm which was very successful and had previously been able to afford high rent for a prime location. Thus the probability that a block in the C.B.D. would receive a business which is relocating is modified to allow for these differences. Considering the factors outlined above each block of the C.B.D. is assigned a probability that reflects the likelihood of that block receiving a business which is moving from the Civic Square Area. The probabilities are then converted to addresses, and each business is assigned a new location according to a random number. This stochastic technique is introduced because it is possible all pertinent factors have not been included or that all ramifications of factors included have not been considered. The number of business which are projected for each block is compared to the actual number of businesses which relocated in that block. In this study Pearsonian Product Moment Correlation results varied from .624 to .654. The model is simple to use and is useful in projecting relocation diffusion patterns of retail businesses resembling the actual relocation diffusion pattern

Decision Support System for Managing Reverse Supply Chain

Reverse logistics are becoming more and more important in the overall Industry area because of the environment and business factors. Planning and implementing a suitable reverse logistics network could bring more profit, customer satisfaction, and an excellent social picture for companies. But, most of the logistics networks are not equipped to handle the return products in reverse channels. Reverse logistics processes and plans rely heavily on reversing the supply chain so that companies can correctly identify and categorize returned products for disposition, an area that offers many opportunities for additional revenue. The science of reverse logistics includes return policy administration, product recall protocols, repairs processing, product repackaging, parts management, recycling, product disposition management, maximizing liquidation values and much more. The focus of this project is to develop a reverse logistics management system/ tools (RLMS). The proposed tools are demonstrated in the following order. First, we identify the risks involved in the reverse supply chain. Survey tool is used to collect data and information required for analysis. The methodologies that are used to identify key risks are the six sigma tools, namely Define, Measure, Analyse, Improve and Control (DMAIC), SWOT analysis, cause and effect, and Risk Mapping. An improved decision-making method using fuzzy set theory for converting linguistic data into numeric risk ratings has been attempted. In this study, the concept of ‘Left and Right dominance approach’(Chen and Liu, 2001) and Method of ‘In center of centroids’ (Thoran et al., 2012a,b) for generalized trapezoidal fuzzy numbers has been used to quantify the ‘degree of risk’ in terms of crisp ratings. After the analysis, the key risks are identified are categorized, and an action requirement plan suggested for providing guidelines for the managers to manage the risk successfully in the context of reverse logistics. Next, from risk assessment findings, information technology risk presents the highest risk impact on the performance of the reverse logistics, especially lack of use of a decision support system (DSS). We propose a novel multi-attribute decision (MADM) support tool that can categorizes return products and make the best alternative selection of recovery and disposal option using carefully considered criteria using MADM decision making methodologies such as fuzzy MOORA and VIKOR. The project can be applied to all types of industries. Once the returned products are collected and categorized at the retailers/ Points of return (PoR), an optimized network is required to determine the number of reprocessing centres to be opened and the optimized optimum material flow between retailers, reprocessing, recycling and disposal centers at minimum costs. The research develops a mixed integer linear programming model for two scenarios, namely considering direct shipping from retailer/ PoR to the respective reprocessing centers and considering the use of centralized return centers (CRC). The models are solved using LINGO 15 software and excel solver tools respectively. The advantage of the implementation of our solution is that it will help improve performance and reduce time. This benefits the company by having a reduction in their cost due to uncertainties and also contributes to better customer satisfaction. Implementation of these tools at ABZ computer distributing company demonstrates how the reverse logistics management tools can used in order to be beneficial to the organization. The tool is designed to be easily implemented at minimal cost and serves as a valuable tool for personnel faced with significant and costly decisions regarding risk assessment, decision making and network optimization in the reverse supply chain practices

Reverse logistics

This paper gives an overview of scientific literature that describes and discusses cases of reverse logistics activities in practice. Over sixty case studies are considered. Based on these studies we are able to indicate critical factors for the practice of reverse logistics. In addition we compare practice with theoretical models and point out research opportunities in the field

EJM Chain Fall Tooling Optimization

The following report describes the progress made by the EJM Chain Fall Tooling Optimization Team since the In-Progress Review. The team has finalized the facility layout design for the chain fall area including the concept of operations, functional requirements, and performance specifications. The scope of the project is completing the new procedures for reducing waste and completing the AutoCAD drawing of the final design. The team researched the objectives accomplished by the new layout design. The goal of the project is to reduce the safety hazards and increase productivity. The team shifted the focus to the salvage, recycling, and waste policy for the chain fall area and the assessment time of the kits﹣kit turns, time needed to assess, amount of inventory. The team estimated the average cost of the missing kits in the chain fall area based on average tool costs. The team estimated the losses of the company for two years (2016 and 2017). Although the team has not currently finished all the cost benefit analysis for each alternative, the team has finalized the outcome of the problem-solving approach for most of the problems found in the chain fall area. The reason for this is that the team is still waiting to receive data from Siemens. After finalizing the design area, the team makes recommendations for future studies based on the limited time to finalize all the proposals made in the report

Business model prototyping for intelligent transport systems: a service-dominant approach

Case Study for Praktijkproef Amsterdam Fase 2 deelproject Zuidoos

OR models in urban service facility location : a critical review of applications and future developments

[EN] Facility location models are well established in various application areas with more than a century of history in academia. Since the 1970s the trend has been shifting from manufacturing to service industries. Due to their nature, service industries are frequently located in or near urban areas that results in additional assumptions, objectives and constraints other than those in more traditional manufacturing location models. This survey focuses on the location of service facilities in urban areas. We studied 110 research papers across different journals and disciplines. We have analyzed these papers on two levels. On the first, we take an Operations Research perspective to investigate the papers in terms of types of decisions, location space, main assumptions, input parameters, objective functions and constraints. On the second level, we compare and contrast the papers in each of these applications categories: (a) Waste management systems (WMS), (b) Large-scale disaster (LSD), (c) Small-scale emergency (SSE), (d) General service and infrastructure (GSI), (e) Non-emergency healthcare systems (NEH) and (f) Transportation systems and their infrastructure (TSI). Each of these categories is critically analyzed in terms of application, assumptions, decision variables, input parameters, constraints, objective functions and solution techniques. Gaps, research opportunities and trends are identified within each category. Finally, some general lessons learned based on the practicality of the models is synthesized to suggest avenues of future research.Ruben Ruiz is partially supported by the Spanish Ministry of Economy and Competitiveness, under the project "SCHEYARD - Optimization of Scheduling Problems in Container Yards (No. DPI2015-65895-R) financed by FEDER funds.Farahani, RZ.; Fallah, S.; Ruiz García, R.; Hosseini, S.; Asgari, N. (2019). OR Models in Urban Service Facility Location: A Critical Review of Applications and Future Developments. European Journal of Operational Research. 276(1):1-27. https://doi.org/10.1016/j.ejor.2018.07.036S127276

A framework to estimate the cost of No-Fault Found events

The article investigates a generic framework to estimate maintenance costs attributed to the No Fault Found (NFF) phenomenon. Such overhead costs are particularly difficult to quantify due to potentially serviceable equipment being returned for repair. Other factors, such as a reduction in the availability of the system, compromising reliability of high value assets, and logistical factors, can all contribute to the cost of resolving an unknown fault. Here we apply the soft systems methodology to capture the critical cost drivers of NFF across the supply chain and build a framework to estimate the cost of NFF. We use a multi-method design including an online survey, workshops and semi-structured interviews to study NFF related cost practices based on information from 12 key participants across 7 UK organisations. The study identifies the major NFF cost drivers across the supply chain (e.g. transportation), the OEM (e.g. inventory) and the customer (e.g. lost man hours). An agent based model is used to evaluate the impact of these cost drivers on the overall NFF cost. The analysis shows how the most appropriate drivers can be selected to represent the cumulative costs due to NFF events and their impacts across the supply network. From the academic perspective, the generic framework for NFF cost estimation demonstrates how qualitative and quantitative information can be used together to achieve maintenance objectives. From a practical perspective, by applying the framework on one component, an organisation has the liberty to analyse the cost of NFF for that particular unit only