Centre de Génie Industriel

The purpose of this paper is, on the one hand, to identify to define and classify customization requirements and, on the other hand, to evaluate how generic modeling and configuration assistance within the Constraint Satisfaction Problem (CSP) framew

International audience

The MISE Project (Mediation Information System Engineering) aims at providing\ncollaborating organizations with a Mediation Information System (MIS) in charge\nof supporting interoperability of a collaborative network. MISE proposes an\noverall MIS design method according to a model-driven approach, based on model\ntransformations. This MIS is in charge of managing (i) information, (ii)\nfunctions and (iii) processes among the information systems (IS) of partner\norganizations involved in the network. Semantic issues are accompanying this\ntriple objective: How to deal with information reconciliation? How to ensure\nthe matching between business functions and technical services? How to identify\nworkflows among business processes? This article aims first, at presenting the\nMISE approach, second at defining the semantic gaps along the MISE approach and\nthird at describing some past, current and future research works that deal with\nthese issues. Finally and as a conclusion, the very "design-oriented" previous\nconsiderations are confronted with "run-time" requirements.\n

Abstract. In the last years, social and organisational aspects of agency have become a major issue in multi-agent systems ’ research. The conducted works may be structured along two main points of view: an agent-centred point of view (ACPV) and an organisation-centred point of view (OCPV). In both approaches the central notion of multi-agent organisation dynamic is considered. In ACPV, this notion leads to a kind of informal, bottom-up, emergent phenomena that we regroup under the general term of self-organisation. In OCPV, this notion gives birth to a huge set of works related to the reorganisation of the formal, top-down, pre-existent organisations that are installed in the MAS. In this paper, we propose to position these two approaches to build a comprehensive picture of organisation dynamic in multi-agent systems. 1

Abstract Curbing habitat loss, reducing fragmentation and restoring connectivity are frequent concerns of conservation planning. In this respect, the incorporation of spatial constraints, fragmentation and connectivity indices into optimization procedures is an important challenge for improving decision support. Here we present a novel optimization approach developed to accurately represent a broad range of conservation planning questions with spatial constraints and landscape indices. Relying on constraint programming, a technique from artificial intelligence based on automatic reasoning, this approach provides both constraint satisfaction and optimality guarantees. We applied this approach in a real case study to support managers of the ‘Côte Oubliée – ‘Woen Vùù – Pwa Pereeù’ provincial park project, in the biodiversity hotspot of New Caledonia. Under budget, accessibility and equitable allocation constraints, we identified restorable areas optimal for reducing forest fragmentation and improving inter‐patch structural connectivity, respectively measured with the effective mesh size and the integral index of connectivity. Synthesis and applications . Our work contributes to more effective and policy‐relevant conservation planning by providing a spatially explicit and problem‐focused optimization approach. By allowing an exact representation of spatial constraints and landscape indices, it can address new questions and ensure whether the solutions will be socio‐economically feasible, through optimality and satisfiability guarantees. Our approach is generic and flexible, thus applicable to a wide range of conservation planning problems, such as ecological restoration planning, reserve or corridor design.

Cellular automata (CA) have been lauded for their ability to generate complex global patterns from simple local rules. The late English mathematician, John Horton Conway, developed his illustrious Game of Life (Life) CA in 1970, which has since remained one of the most quintessential CA constructions-capable of producing a myriad of complex dynamic patterns and computational universality. Life and several other Life-like rules have been classified in the same group of aesthetically and dynamically interesting CA rules characterized by their complex behaviors. However, a rigorous quantitative comparison among similarly classified Life-like rules has not yet been fully established. Here we show that Life is capable of maintaining as much complexity as similar rules while remaining the most parsimonious. In other words, Life contains a consistent amount of complexity throughout its evolution, with the least number of rule conditions compared to other Life-like rules. We also found that the complexity of higher density Life-like rules, which themselves contain the Life rule as a subset, form a distinct concave density-complexity relationship whereby an optimal complexity candidate is proposed. Our results also support the notion that Life functions as the basic ingredient for cultivating the balance between structure and randomness to maintain complexity in 2D CA for low- and high-density regimes, especially over many iterations. This work highlights the genius of John Horton Conway and serves as a testament to his timeless marvel, which is referred to simply as: Life.

An analytical method has been developed for the determination of glyphosate herbicide and its metabolite aminomethylphosphonic acid (AMPA) in natural waters to a level of 0.10 µg/L with a good linearity in the range 0.10-2.00µg/L and coefficients of variation under 20 % for each spiked level.The procedure involves a precolumn derivatization step with 9-fluorenylmethylchloroformate (FMOC-Cl) yielding highly fluorescent derivatives of the analytes which then can be determined by HPLC with fluorescence detection.The method is used for analysis of natural (surface and ground) and treated waters.Matrice effects have been pointed out, particularly the effects of hard ionic content and the effects of chlorine residues into treated waters.

Abstract Context Measuring intra-patch connectivity, i.e. the connectivity within a habitat patch, is important to evaluate landscape fragmentation and connectivity. However, intra-patch connectivity is mainly measured with patch size, which can conceal diverse intra-patch connectivity patterns for similar patch size distributions. Objectives We suggest a method to refine the intra-patch connectivity component of fragmentation and connectivity indices. This method allows for distinguishing different intra-patch connectivity patterns for similar patch size distributions. Methods We used normalized patch complexity indices to weight patch size in common fragmentation and connectivity indices. Patch complexity indices included two existing geometrical indices (SHAPE and FRAC), and a new index derived from spatial network analysis, the mean detour index (MDI). We analyzed the behaviours of adjusted fragmentation and connectivity indices theoretically and empirically on both artificial and real landscapes. Results While maintaining the mathematical properties of fragmentation and connectivity indices, our method could distinguish landscapes with identical patch size distributions but different spatial configurations. The mean detour index had a different response than geometrical indices. This result indicates that, at the patch level, topological complexity can exhibit different patterns from geometrical complexity. Conclusions Measuring intra-patch connectivity with patch size in fragmentation and connectivity indices cannot distinguish landscapes having similar patch sizes distribution but different spatial configurations. This paper introduces a method to distinguish such patterns relying on geometrical and topological indices and shows to which extent it can impact conservation planning.

Since the quality of products is a major concern in production systems, implementing efficient inspection policies is of great importance to reduce quality-related costs. This article addresses the problem of finding optimal inspection policies in serial multistage production processes to minimise total inspection cost where the cost components are described by the use of fuzzy numbers. The type of inspection in each stage and the acceptance limits are considered as decision variables. The size of sample to inspect, where sampling inspection is adopted, is also incorporated into the model as the third decision parameter. The case in which the inspectors are not error-free is examined, as well. A solution algorithm is proposed based on particle swarm optimisation, and simulation is used to provide better insight into the optimal solution. Numerical experiments discussed in different settings illustrate the applicability and efficiency of the proposed approach.

Software effort estimation is a crucial task in the software project management. It is the basis for subsequent planning, control, and decision-making. Reliable effort estimation is difficult to achieve, especially because of the inherent uncertainty arising from the noise in the dataset used for model elaboration and from the model limitations. This research paper proposes a software effort estimation method that provides realistic effort estimates by taking into account uncertainty in the effort estimation process. To this end, an approach to introducing uncertainty in Neural Network based effort estimation model is presented. For this purpose, bootstrap resampling technique is deployed. The proposed method generates a probability distribution of effort estimates from which the Prediction Interval associated to a confidence level can be computed. This is considered to be a reasonable representation of reality, thus helping project managers to make well-founded decisions. The proposed method has been applied on a dataset from International Software Benchmarking Standards Group and has shown better results compared to traditional effort estimation based on linear regression.

Abstract Neutral landscape models have many applications in ecology, such as supporting spatially explicit simulations, developing and evaluating landscape indices. However, current approaches provide few options to produce large landscapes with controlled composition and fragmentation indices. We introduce flsgen (Fragmented Landscape Generator), a new neutral landscape generator that addresses this limitation by providing a high level of control over 14 landscape indices. The main novelty of flsgen is the decomposition of landscape generation into two steps: the solving of a constraint satisfaction problem and the generation of a landscape raster with a stochastic algorithm. The latter relies on a continuous environmental gradient that influences the landscape's spatial configuration. flsgen can generate fine‐grained artificial landscapes in small amounts of time, which makes it suited to produce large landscape series systematically. We demonstrate the features of flsgen through three illustrative use cases. flsgen is a practical and efficient tool that expands the current possibilities of neutral landscape models and widens their potential applications. To facilitate its uptake, flsgen is available as free and open‐source software through a Java API, a command‐line interface or an R package.

12th IFAC Symposium on Information Control Problems in Manufacturing (INCOM 2006), St Etienne, FRANCE, MAY 17-JUL 19, 2006

Safety analysis of railway CBTC systems aims at finding and validating failure scenarios. In this article we present a scenario-based FMEA method based on ScOLA, a scenario oriented modeling language dedicated to the analysis and formalization of complex systems. The specifications of such systems are usually spread in documents of thousands of pages written in a natural language. These documents are the basis for the safety analysis and validations activities. Therefore, we propose the scenario-based FMEA method to perform safety analysis that is more efficient than the paper-based analysis. The method retrieves and evaluates failure scenarios using functional ones. The article aims at presenting the method and its application on a railway system.

Business intelligence (BI) as a paradigm with methods and tools substantially improves decisions with regard to business evolutions. Through the emerging business process management approaches, it becomes possible to link BI-tools with the underlying process models. This paper explains how process models can be enriched with risk models in the context of business intelligence.

The current evolution of Information Technology leads to the increase of automatic data processing over multiple information systems. In this context, the lack of user’s control on their personal data leads to the crucial question of their privacy preservation. A typical example concerns the disclosure of confidential identity information, without the owner’s agreement. This problem is stressed in multi-agent systems (MAS) where users delegate their control on their personal data to autonomous agents. Interaction being one of the main mechanism in MAS, sensitive information exchange and processing are a key issue with respect to privacy. In this article, we propose a model, ”Hippocratic Multi-Agent System” (HiMAS), to tackle this problem. This model defines a set of principles bearing on an agency to preserve privacy. In order to illustrate our model, we have chosen the concrete application of decentralized calendars management.

Nowadays organisations are subjects to frequent changes requiring continuous alignment of business processes. In the adaptive digital business ecosystems (DBEs), agile value chains and the cluster-based bundling of business partners are an essential characteristic. While the resulting flexibility holds opportunities, it increases initially uncertainty. In order to support such organisations to increase their maturity, we suggest a synchronisation of the lifecycles of process management and risk management by integrating both processes. This integration is based on a common modelling language. From the process management perspective, there are number of semi-formal modelling languages while these are missing for risk management. This paper is about a semi-formal modelling language supporting collaboration between the risk management team and the process management one. The synchronised lifecycle appears therefore as the collaboration mechanism coordinating the activities of the heterogeneous team.

This paper deals with aiding preliminary design when considered as a constraint satisfaction problem (CSP). In this case, constraint filtering techniques provide some kind of interactive assistance to the designer. However, some kinds of numerical constraints corresponding with numerical relations cannot be filtered precisely with classical analytical filtering techniques such as interval arithmetic or box-consistency; it is therefore necessary to discretize them in order to include them in the CSP. To this end, quad trees (QT) have been proposed for binary constraints, or 2k trees when more than two variables are considered; but QT assume that a constraint must be defined by a single numerical function. The aim of this paper is to show that QT techniques can be extended when a constraint is defined by a piecewise function or by a set of numerical functions defined on intervals. The first section recalls some basics relevant to the preliminary design problem and the interests of the CSP assistance. The second section presents the principles of the QT. The last section describes our contributions relevant to QT extensions dealing with piecewise functions.

Ecological restoration is essential to curb the decline of biodiversity and ecosystems worldwide. Since the resources available for restoration are limited, restoration efforts must be cost‐effective to achieve conservation outcomes. Although decision support tools are available to aid in the design of protected areas, little progress has been made to provide such tools for restoration efforts. Here, we introduce the restoptr R package, a decision support tool designed to identify priority areas for ecological restoration. It uses constraint programming—an artificial intelligence technique—to identify optimal plans given ecological and socioeconomic constraints. Critically, it can identify strategic locations to enhance connectivity and reduce fragmentation across a broader landscape using complex landscape metrics. We illustrate its usage with a case study in New Caledonia. By applying this tool, we identified priority areas for restoration that could reverse forest fragmentation induced by mining activities in a specific area. We also found that relatively small investments could deliver large returns to restore connectivity. The restoptr R package is a free and open‐source decision support tool available on the Comprehensive R Archive Network ( https://cran.r-project.org/package=restoptr ).

Small-medium enterprises (SMEs) gain their strengths from flexible market orientation, agile value chains and cluster-based innovation capacity. The changing global business environment challenges organizations to aim for agility and performance driven management through process focused thinking. For the future collaboration of SMEs with their partners, the agility aim of the Digital Ecosystem paradigm demands for an explicit risk management and collaboration support. This involves an explicit management of the business process by combining continuous process improvement and process reengineering. However, the outcome of process management effort is risky because of the lack of operational information about the future process. The paper analyzes the possible contribution of risk management to support the management of business processes in order to increase the maturity of organizations. The concept is applied in a process simulation example for furniture production. Collaboration support is provided to allow the real-time sharing and interaction of the parties involved, e.g. in case of deviations from the agreed upon target process.

A design of DSS for mass production machining systems In this paper, we present a decision support tool (DSS) for preliminary design of transfer machines with rotary or mobile tables. In these transfer machines, the machining operations are executed on working positions equipped by standard multi-spindle heads. A part is sequentially machined on m working positions and is moved from one position to the next using a rotary or a mobile table. The operations are grouped into blocks, where the operations of the same block are simultaneously performed by one multi-spindle head. At the preliminary design stage, the goal is to select the number of working positions and to decide which spindle heads will be installed minimizing the machine cost while respecting a given production rate. The paper presents the overall approach and depicts mathematical and decision-support methods developed and implemented in a software for the optimization of preliminary design (or reconfiguration) of such machining systems.