Towards a Novel Cooperative Logistics Information System Framework

Supply Chains and Logistics have a growing importance in global economy. Supply Chain Information Systems over the world are heterogeneous and each one can both produce and receive massive amounts of structured and unstructured data in real-time, which are usually generated by information systems, connected objects or manually by humans. This heterogeneity is due to Logistics Information Systems components and processes that are developed by different modelling methods and running on many platforms; hence, decision making process is difficult in such multi-actor environment. In this paper we identify some current challenges and integration issues between separately designed Logistics Information Systems (LIS), and we propose a Distributed Cooperative Logistics Platform (DCLP) framework based on NoSQL, which facilitates real-time cooperation between stakeholders and improves decision making process in a multi-actor environment. We included also a case study of Hospital Supply Chain (HSC), and a brief discussion on perspectives and future scope of work

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Towards a Novel Cooperative Logistics Information System Framework

International audienceSupply Chains and Logistics have a growing importance in global economy. Supply Chain Information Systems over the world are heterogeneous and each one can both produce and receive massive amounts of structured and unstructured data in real-time, which are usually generated by information systems, connected objects or manually by humans. This heterogeneity is due to Logistics Information Systems components and processes that are developed by different modelling methods and running on many platforms; hence, decision making process is difficult in such multi-actor environment. In this paper we identify some current challenges and integration issues between separately designed Logistics Information Systems (LIS), and we propose a Distributed Cooperative Logistics Platform (DCLP) framework based on NoSQL, which facilitates real-time cooperation between stakeholders and improves decision making process in a multi-actor environment. We included also a case study of Hospital Supply Chain (HSC), and a brief discussion on perspectives and future scope of work

Selecting Algorithms for the Efficient Solving of Large Berth Allocation Problems

International audienceIn this presentation, the algorithm selection for the berth allocation problem (BAP) under solution time limits is considered. BAP consists in scheduling ships on berths subject to ready times and ship size constraints, in minimum turnaround time. For the purposes of strategic port capacity planning, BAP must be solved many times in extensive simulations, needed to account for uncertainties on ship traffic, handling times, and also to consider alternative terminal designs. Exact methods exist that solve BAP problems on medium size instances in a few minutes. However, theses methods cannot be adapted to solve many large instances in a short time limit. Even metaheuristics may be too consuming in this setting. The Algorithm Selection Problem (ASP) is the challenge of selecting algorithms with the best overall performance for the considered application. An approach is proposed here to select a portfolio of algorithms, that will each solve the considered BAP instances and return good solutions. The portfolio is built thanks to training instances. The performance is measured by runtime and solution quality. A linear program minimizing the solution quality loss, subject to overall runtime limit, is used to select the portfolio. Thus, the portfolio evolves with changing runtime limits, which is a key design decision in the simulations. For the training and validating datasets, random instances and real ship traffic logs are used. In our experimental study, a portfolio of heuristics is developed which can be used to solve efficiently very large instances of BAP, emerging when time horizons of months or years come into consideration. The evolution of the algorithm portfolios under changing runtime limits as well as their ability to solve new instances are studied

A PROPOSAL OF NOSQL ENABLED LOGISTICS INFORMATION SYSTEM FRAMEWORK

International audienceSupply Chains and Logistics have a growing importance in global economy. Supply chains over the world are very heterogeneous and each one can both produce and receive massive amounts of structured and unstructured data in real-time, which are usually generated by information systems, smart objects or manually by humans. This heterogeneity is due to Logistics Systems components and processes that are developed by different modelling methods and running on many platforms. In this paper we attempt to identify current challenges and integration issues between separately designed Information and Communication Technology systems and we propose a distributed NoSQL based Logistics Information System architecture that facilitate real-time cooperation between stakeholders in a multi-actor environment. We included also a brief discussion on perspectives and future scope of work

Stochastic scheduling with variable profile and precedence constraints

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Preemptive scheduling with variable profile, precedence constraints and due dates

This paper is concerned with the problem of scheduling preemptive tasks subject to precedence constraints in order to minimize the maximum lateness and the makespan. The number of available parallel processors is allowed to vary in time. It is shown that when an earliest due date first algorithm provides an optimal nonpreemptive schedule for unit execution time tasks, then the preemptive priority scheduling algorithm, referred to as smallest laxity first, provides an optimal preemptive schedule for real-execution-time tasks. When the objective is to minimize the makespan, we get the same kind of result between highest level first schedules solving nonpremptive tasks with unit execution time and the longest remaining path first schedule for the corresponding preemptive scheduling problem with real-execution-time tasks. These results are applied to four specific profile scheduling problems and new optimality results are obtained

Modelling a Multi-Modal Logistic Network with Agents and Dynamic Graphs

International audienceThis paper presents a model of a logistic system. Our goal is to understand how such a system (with numerous stakeholders) behaves and evolves according to different constraints or scenarios. We adopted a complex system approach which leads us to propose an agent-based model coupled with dynamic graphs. It allows us to represent the properties, constraints and behaviours at a local level of a logistic system in order to reproduce the global behaviours thanks to the simulation in a dynamic context. The simulation (which uses data about the Seine axis) allows to test different scenarios in order to understand how local decisions impact the whole system. For example, this work presents the evolution of the system at the opening of the Seine-Nord Europe Canal. Indeed, this canal is a real major project for Europe, and has numerous economical stakes. So, we first describe the traffic evolution on the multi-modal transportation network (see figures 1 to 4). Then, we observe different other measures (evolution of costs, transportation mode share). Thanks to these analyses, we show that the Seine-Nord Europe Canal should promote the use of the river barges and reduce financial costs. In the same time, it could modify the respective shares of the northern European ports

Selective predisposition to bacterial infections in IRAK-4–deficient children: IRAK-4–dependent TLRs are otherwise redundant in protective immunity

Human interleukin (IL) 1 receptor–associated kinase 4 (IRAK-4) deficiency is a recently discovered primary immunodeficiency that impairs Toll/IL-1R immunity, except for the Toll-like receptor (TLR) 3– and TLR4–interferon (IFN)-a/b pathways. The clinical and immunological phenotype remains largely unknown. We diagnosed up to 28 patients with IRAK-4 deficiency, tested blood TLR responses for individual leukocyte subsets, and TLR responses for multiple cytokines. The patients' peripheral blood mononuclear cells (PBMCs) did not induce the 11 non-IFN cytokines tested upon activation with TLR agonists other than the nonspecific TLR3 agonist poly(I:C). The patients' individual cell subsets from both myeloid (granulocytes, monocytes, monocyte-derived dendritic cells [MDDCs], myeloid DCs [MDCs], and plasmacytoid DCs) and lymphoid (B, T, and NK cells) lineages did not respond to the TLR agonists that stimulated control cells, with the exception of residual responses to poly(I:C) and lipopolysaccharide in MDCs and MDDCs. Most patients (22 out of 28; 79%) suffered from invasive pneumococcal disease, which was often recurrent (13 out of 22; 59%). Other infections were rare, with the exception of severe staphylococcal disease (9 out of 28; 32%). Almost half of the patients died (12 out of 28; 43%). No death and no invasive infection occurred in patients older than 8 and 14 yr, respectively. The IRAK-4–dependent TLRs and IL-1Rs are therefore vital for childhood immunity to pyogenic bacteria, particularly Streptococcus pneumoniae. Conversely, IRAK-4–dependent human TLRs appear to play a redundant role in protective immunity to most infections, at most limited to childhood immunity to some pyogenic bacteria

Nearly on line scheduling of preemptive independent tasks

AbstractWe discuss the problem of scheduling preemptive independent tasks, subject to release dates and due dates, on identical processors, so as to minimize the maximum lateness. This problem was solved by a polynomial flow based algorithm, but the major drawback of this approach is its off-line character. We study a priority algorithm, the equivalent of a list scheduling method in the non-preemptive case, in which tasks are ordered according to their due dates. This algorithm is nearly on-line and of low complexity. It builds an optimal schedule when the release dates are equal. In the general case, it provides an absolute performance guarantee. These results hold when the number of available machines is allowed to vary with time in a zigzag way (the number of machines is either K, or K − 1)