Theorizing and Generalizing About Risk Assessment and Regulation Through Comparative Nested Analysis of Representative Cases

This article provides a framework and offers strategies for theorizing and generalizing about risk assessment and regulation developed in the context of an on-going comparative study of regulatory behavior. Construction of a universe of nearly 3,000 risks and study of a random sample of 100 of these risks allowed us to estimate relative U.S. and European regulatory precaution over a thirty-five-year period. Comparative nested analysis of cases selected from this universe of ecological, health, safety, and other risks or its eighteen categories or ninety-two subcategories of risk sources or causes will allow theory-testing and -building and many further descriptive and causal comparative generalizations

Hybrid Meta-Heuristics for Robust Scheduling

The production and delivery of rapidly perishable goods in distributed supply networks involves a number of tightly coupled decision and optimization problems regarding the just-in-time production scheduling and the routing of the delivery vehicles in order to satisfy strict customer specified time-windows. Besides dealing with the typical combinatorial complexity related to activity assignment and synchronization, effective methods must also provide robust schedules, coping with the stochastic perturbations (typically transportation delays) affecting the distribution process. In this paper, we propose a novel metaheuristic approach for robust scheduling. Our approach integrates mathematical programming, multi-objective evolutionary computation, and problem-specific constructive heuristics. The optimization algorithm returns a set of solutions with different cost and risk tradeoffs, allowing the analyst to adapt the planning depending on the attitude to risk. The effectiveness of the approach is demonstrated by a real-world case concerning the production and distribution of ready-mixed concrete.Meta-Heuristics;Multi-Objective Genetic Optimization;Robust Scheduling;Supply Networks

Strategic marketing, production, and distribution planning of an integrated manufacturing system

Production Scheduling;Distribution;CIM;production

04231 Abstracts Collection -- Scheduling in Computer and Manufacturing Systems

During 31.05.-04.06.04, the Dagstuhl Seminar 04231 "Scheduling in Computer and Manufacturing Systems" was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Sharing Economy Last Mile Delivery: Three Essays Addressing Operational Challenges, Customer Expectations, and Supply Uncertainty

Last mile delivery has become a critical competitive dimension facing retail supply chains. At the same time, the emergence of sharing economy platforms has introduced unique operational challenges and benefits that enable and inhibit retailers’ last mile delivery goals. This dissertation investigates key challenges faced by crowdshipping platforms used in last mile delivery related to crowdsourced delivery drivers, driver-customer interaction, and customer expectations. We investigate the research questions of this dissertation through a multi-method design approach, complementing a rich archival dataset comprised of several million orders retrieved from a Fortune 100 retail crowdshipping platform, with scenario-based experiments. Specifically, the first study analyzes the impact of delivery task remuneration and operational characteristics that impact drivers’ pre-task, task, and post-task behaviors. We found that monetary incentives are not the sole factor influencing drivers’ behaviors. Drivers also consider the operational characteristics of the task when accepting, performing, and evaluating a delivery task. The second study examines a driver’s learning experience relative to a delivery task and the context where it takes place. Results show the positive impact of driver familiarity on delivery time performance, and that learning enhances the positive effect. Finally, the third study focuses on how delivery performance shape customers’ experience and future engagement with the retailer, examining important contingency factors in these relationships. Findings support the notion that consumers time-related expectations on the last mile delivery service influence their perceptions of the delivery performance, and their repurchase behaviors. Overall, this dissertation provides new insights in this emerging field that advance theory and practice

Sharing Economy Last Mile Delivery: Three Essays Addressing Operational Challenges, Customer Expectations, and Supply Uncertainty

Last mile delivery has become a critical competitive dimension facing retail supply chains. At the same time, the emergence of sharing economy platforms has introduced unique operational challenges and benefits that enable and inhibit retailers’ last mile delivery goals. This dissertation investigates key challenges faced by crowdshipping platforms used in last mile delivery related to crowdsourced delivery drivers, driver-customer interaction, and customer expectations. We investigate the research questions of this dissertation through a multi-method design approach, complementing a rich archival dataset comprised of several million orders retrieved from a Fortune 100 retail crowdshipping platform, with scenario-based experiments. Specifically, the first study analyzes the impact of delivery task remuneration and operational characteristics that impact drivers’ pre-task, task, and post-task behaviors. We found that monetary incentives are not the sole factor influencing drivers’ behaviors. Drivers also consider the operational characteristics of the task when accepting, performing, and evaluating a delivery task. The second study examines a driver’s learning experience relative to a delivery task and the context where it takes place. Results show the positive impact of driver familiarity on delivery time performance, and that learning enhances the positive effect. Finally, the third study focuses on how delivery performance shape customers’ experience and future engagement with the retailer, examining important contingency factors in these relationships. Findings support the notion that consumers time-related expectations on the last mile delivery service influence their perceptions of the delivery performance, and their repurchase behaviors. Overall, this dissertation provides new insights in this emerging field that advance theory and practice

Hybrid Meta-Heuristics for Robust Scheduling

The production and delivery of rapidly perishable goods in distributed supply networks involves a number of tightly coupled decision and optimization problems regarding the just-in-time production scheduling and the routing of the delivery vehicles in order to satisfy strict customer specified time-windows. Besides dealing with the typical combinatorial complexity related to activity assignment and synchronization, effective methods must also provide robust schedules, coping with the stochastic perturbations (typically transportation delays) affecting the distribution process. In this paper, we propose a novel metaheuristic approach for robust scheduling. Our approach integrates mathematical programming, multi-objective evolutionary computation, and problem-specific constructive heuristics. The optimization algorithm returns a set of solutions with different cost and risk tradeoffs, allowing the analyst to adapt the planning depending on the attitude to risk. The effectiveness of the approach is demonstrated by a real-world case concerning the production and distribution of ready-mixed concrete

Quantum inspired approach for early classification of time series

Is it possible to apply some fundamental principles of quantum-computing to time series classi\ufb01cation algorithms? This is the initial spark that became the research question I decided to chase at the very beginning of my PhD studies. The idea came accidentally after reading a note on the ability of entanglement to express the correlation between two particles, even far away from each other. The test problem was also at hand because I was investigating on possible algorithms for real time bot detection, a challenging problem at present day, by means of statistical approaches for sequential classi\ufb01cation. The quantum inspired algorithm presented in this thesis stemmed as an evolution of the statistical method mentioned above: it is a novel approach to address binary and multinomial classi\ufb01cation of an incoming data stream, inspired by the principles of Quantum Computing, in order to ensure the shortest decision time with high accuracy. The proposed approach exploits the analogy between the intrinsic correlation of two or more particles and the dependence of each item in a data stream with the preceding ones. Starting from the a-posteriori probability of each item to belong to a particular class, we can assign a Qubit state representing a combination of the aforesaid probabilities for all available observations of the time series. By leveraging superposition and entanglement on subsequences of growing length, it is possible to devise a measure of membership to each class, thus enabling the system to take a reliable decision when a suf\ufb01cient level of con\ufb01dence is met. In order to provide an extensive and thorough analysis of the problem, a well-\ufb01tting approach for bot detection was replicated on our dataset and later compared with the statistical algorithm to determine the best option. The winner was subsequently examined against the new quantum-inspired proposal, showing the superior capability of the latter in both binary and multinomial classi\ufb01cation of data streams. The validation of quantum-inspired approach in a synthetically generated use case, completes the research framework and opens new perspectives in on-the-\ufb02y time series classi\ufb01cation, that we have just started to explore. Just to name a few ones, the algorithm is currently being tested with encouraging results in predictive maintenance and prognostics for automotive, in collaboration with University of Bradford (UK), and in action recognition from video streams

Etude du développement spatio-temporelle d'un plant de fraisier

In strawberry, the balance between flowering and vegetative development, including the production of stolons (elongated stems carrying the daughter plants), conditions the yield of the plant. The objective of the thesis was to better understand the developmental processes of strawberry plant, namely flowering, the vegetative development of axes and runnering, through a spatio-temporal study. Three complementary approaches have been developed on seasonal flowering varieties planted in "soilless" conditions: (1) modeling the weekly emergence of flowers, leaves and stolons by a longitudinal segmentation analysis, (2) spatio-temporal analysis of plant architecture during a seasonal production and (3) expression of key genes related to flowering. (1) Univariate multiple change-point models applied to each phenological variable were based on the assumption that phase changes were synchronous between individuals of a given variety. These models allowed to identify phases for each variety and each type of organ. Multivariate multiple changepoint models combining the three types of organ highlighted a strong structuring of strawberry development by flowering and runnering. Moreover, the varieties can be grouped into two profiles of flowering with the presence or not of a second period of flowering. Finally, the stolon emergence models show a synchronism suggesting a strong environmental effect. (2) Spatio-temporal analysis of the architecture relied on a multi-scale tree graph allowing visual representation and topological analysis of plant development. This analysis revealed early topological differences as well as different strategies of development between varieties. These differences in development partially explain the different flowering patterns. (3) Among the genes studied for their expression during the cultivation of strawberry plants, SUPPRESSOR OF OVEREXPRESSION OF CONSTANS1 (SOC1) appears as a marker of vegetative development and stolon emergence. An architectural approach was also initiated on the diploid strawberry. First results allowed to better specify the fate of axillary meristems. In conclusion, this work allowed to evaluate the varieties in production condition and to identify selection criteria for the development of new varieties. It has also allowed the development of new tools that can be used by breeders and experimenters.Chez le fraisier la balance entre floraison et développement végétatif incluant la production de stolons (tiges allongées portant les plants filles) conditionne le rendement du plant. L’objectif de la thèse était d’obtenir une meilleure compréhension des processus de développement du fraisier, la floraison, le développement végétatif des axes et le stolonnage, grâce à une étude spatio-temporelle. Trois approches complémentaires ont été développées sur six variétés non-remontantes plantées en conditions « hors sol » : (1) la modélisation des profils d’émergence hebdomadaire de fleurs, feuilles et stolons par une analyse de segmentation longitudinale, (2) l’analyse spatio-temporelle de l’architecture des plants durant une saison de production et (3) le suivi de l’expression de gènes clés liés à la floraison. (1) Les modèles univariés de détection de ruptures appliqués à chaque variable phénologique étaient basés sur l’hypothèse que les changements de phases sont synchrones entre les individus d’une même variété. Ces modèles ont permis d’identifier des phases pour chacune des variétés et chacun des trois types d’organe. Les modèles de détection de ruptures multivariés combinant les trois types d’organes ont permis de mettre en évidence une forte structuration du développement du fraisier par la floraison et le stolonnage. De plus, les variétés se regroupent autour de deux profils de floraison avec la présence ou pas d’un deuxième pic de floraison. Enfin, les modèles d’émergence de stolon montrent un synchronisme suggérant un fort effet environnemental. (2) L’analyse spatio-temporelle de l’architecture s’est basée sur un modèle de graphe arborescent multi-échelle, permettant une représentation visuelle et une analyse de la topologie du plant au cours de son développement. Cette analyse a permis de mettre en évidence des différences topologiques précoces ainsi que différentes stratégies de développement entre les variétés. Ces différences de développement expliquent en partie les différents profils de floraison. (3) Parmi les gènes étudiés pour leur expression au cours de la culture des plants de fraisier, SUPPRESSOR OF OVEREXPRESSION OF CONSTANS1 (SOC1) apparait comme un marqueur de développement végétatif et de l’émergence des stolons. Une approche architecturale a également été initiée sur le fraisier diploïde. Les premiers résultats ont permis de mieux préciser le devenir des méristèmes axillaires. En conclusion, ce travail a permis d’évaluer les variétés en condition de production et d’identifier des critères de sélection pour le développement de nouvelles variétés. Il a également permis de développer de nouveaux outils qui pourront être utilisés par les sélectionneurs et les expérimentateurs