367 research outputs found

    Using criticalities as a heuristic for Answer Set Programming

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    Answer Set Programming is a new paradigm based on logic programming. The main component of answer set programming is a system that finds the answer sets of logic programs. Generally, systems utilize some heuristics to choose new literals at the choice points. The heuristic used in this process is one of the key factors for the performance of the system. A new heuristic for answer set programming has been developed. This heuristic is inspired by hierarchical planning. The notion of criticality, which was introduced for generating abstraction hierarchies in hierarchical planning, is used in this heuristic. The resulting system (CSMODELS) uses this new heuristic and is based on the system SMODELS. The experimental results show that this new heuristic is promising for answer set programming. CSMODELS generally takes less time than SMODELS to find an answer set

    Project scheduling with multi skilled resources: a conceptual framework

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    Projects’ success depends, mostly, on people’s motivation and competences. A good plan is essential, but it is insufficient if the project manager is incapable to dynamically reassign people to project’s tasks, so as to create multi-skilled teams and to avoid multi-tasking and over-allocation. In this regard, several models dealing with the “Multi Skilled Work Force Scheduling Problem” have been proposed, but unfortunately, most of the works produced so far has not yet found its way into practice. This is mainly because project scheduling and resources allocation are jointly considered, a fact that leads to complex and rigid mathematical formulations and that poses serious constraints on the precision of the input data. Since projects are, by their very nature, uncertain entities, we believe that it is preferable to abandon the over optimistic idea of a global optimum, in favour of a suboptimal but stable and feasible solution. To this aim the paper proposes a heuristic framework that extends the well-known “Dynamic Scheduling” approach. Specifically, the problem is tackled in a hierarchical way: project scheduling is solved first and resource allocation is solved next, considering tasks durations as fixed constraints. In doing so, our focus is on the resources allocation phase, and the objective is to assure an almost perfect matching between resources’ skills and tasks requirements, so as to assure project quality and, also, a harmonious development of the workforce. Possible approaches, based on mathematical programming, which could be easily implemented in project management software, are presented and discussed

    Expect the unexpected: Sub-second optimization for segment routing

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    In this paper, we study how to perform traffic engineering at an extremely-small time scale with segment routing, addressing a critical need for modern wide area networks. Prior work has shown that segment routing enables to better engineer traffic, thanks to its ability to program detours in forwarding paths, at scale. Two main approaches have been explored for traffic engineering with segment routing, respectively based on integer linear programming and constraint programming. However, no previous work deeply investigated how quickly those approaches can react to unexpected traffic changes and failures. We highlight limitations of existing algorithms, both in terms of required execution time and amount of path changes to be applied. Thus, we propose a new approach, based on local search and focused on the quick re-arrangement of (few) forwarding paths. We describe heuristics for sub-second recomputation of segment-routing paths that comply with requirements on the maximum link load (e.g., for congestion avoidance). Our heuristics enable a prompt answer to sudden criticalities affecting network services and business agreements. Through extensive simulations, we indeed experimentally show that our proposal significantly outperforms previous algorithms in the context of time-constrained optimization, supporting radical traffic changes in few tens of milliseconds for realistic networks

    Integrated Models and Tools for Design and Management of Global Supply Chain

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    In modern and global supply chain, the increasing trend toward product variety, level of service, short delivery delay and response time to consumers, highlight the importance to set and configure smooth and efficient logistic processes and operations. In order to comply such purposes the supply chain management (SCM) theory entails a wide set of models, algorithms, procedure, tools and best practices for the design, the management and control of articulated supply chain networks and logistics nodes. The purpose of this Ph.D. dissertation is going in detail on the principle aspects and concerns of supply chain network and warehousing systems, by proposing and illustrating useful methods, procedures and support-decision tools for the design and management of real instance applications, such those currently face by enterprises. In particular, after a comprehensive literature review of the principal warehousing issues and entities, the manuscript focuses on design top-down procedure for both less-than-unit-load OPS and unit-load storage systems. For both, decision-support software platforms are illustrated as useful tools to address the optimization of the warehousing performances and efficiency metrics. The development of such interfaces enables to test the effectiveness of the proposed hierarchical top-down procedure with huge real case studies, taken by industry applications. Whether the large part of the manuscript deals with micro concerns of warehousing nodes, also macro issues and aspects related to the planning, design, and management of the whole supply chain are enquired and discussed. The integration of macro criticalities, such as the design of the supply chain infrastructure and the placement of the logistic nodes, with micro concerns, such the design of warehousing nodes and the management of material handling, is addressed through the definition of integrated models and procedures, involving the overall supply chain and the whole product life cycle. A new integrated perspective should be applied in study and planning of global supply chains. Each aspect of the reality influences the others. Each product consumed by a customer tells a story, made by activities, transformations, handling, processes, traveling around the world. Each step of this story accounts costs, time, resources exploitation, labor, waste, pollution. The economical and environmental sustainability of the modern global supply chain is the challenge to face

    LEAP Product and Manufacturing Design Support System

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    The aim of this chapter is to show the development of the so-called "LEAP model for design support." The introduction highlights the importance of pursuing a product life cycle approach during the design phase, in order to gain economic and environmental impact savings. We use the life cycle costing and life cycle assessment methodologies, which we will define and criticize. In the light of the gaps identified, this chapter presents the life cycle optimization model, highlighting its development and implementation. We will also describe a first application in the industrial context, referred to as the COMAU use case. Finally, our conclusion summarizes the results and suggests possible extensions of the model

    Machine learning and its applications in reliability analysis systems

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    In this thesis, we are interested in exploring some aspects of Machine Learning (ML) and its application in the Reliability Analysis systems (RAs). We begin by investigating some ML paradigms and their- techniques, go on to discuss the possible applications of ML in improving RAs performance, and lastly give guidelines of the architecture of learning RAs. Our survey of ML covers both levels of Neural Network learning and Symbolic learning. In symbolic process learning, five types of learning and their applications are discussed: rote learning, learning from instruction, learning from analogy, learning from examples, and learning from observation and discovery. The Reliability Analysis systems (RAs) presented in this thesis are mainly designed for maintaining plant safety supported by two functions: risk analysis function, i.e., failure mode effect analysis (FMEA) ; and diagnosis function, i.e., real-time fault location (RTFL). Three approaches have been discussed in creating the RAs. According to the result of our survey, we suggest currently the best design of RAs is to embed model-based RAs, i.e., MORA (as software) in a neural network based computer system (as hardware). However, there are still some improvement which can be made through the applications of Machine Learning. By implanting the 'learning element', the MORA will become learning MORA (La MORA) system, a learning Reliability Analysis system with the power of automatic knowledge acquisition and inconsistency checking, and more. To conclude our thesis, we propose an architecture of La MORA

    Design of a distributed supply chain for spare parts

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    Process-mining-enabled audit of information systems: Methodology and an application

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    Current methodologies for Information Systems (ISs) audits suffer from some limitations that could question the effectiveness of such procedures in detecting deviations, frauds, or abuses. Process Mining (PM), a set of business-process-related diagnostic and improvement techniques, can tackle these weaknesses, but literature lacks contributions that address this possibility concretely. Thus, by framing PM as an Expert System (ES) engine, this paper presents a five-step PM-based methodology for IS audits and validates it through a case in a freight export port process managed by a Port Community System (PCS), an open electronic platform enabling information exchange among port stakeholders. The validation pointed out some advantages (e.g. depth of analysis, easier automation, less invasiveness) of our PM-enabled methodology over extant ESs and tools for IS audit. The substantive test and the check on the PCS processing controls and output controls allowed to identify four major non-conformances likely implying both legal and operational risks, and two unforeseen process deviations that were not known by the port authority, but that could improve the flexibility of the process. These outcomes set the stage for an export process reengineering, and for revising the boundaries in the process flow of the PCS
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