Production/maintenance cooperative scheduling using multi-agents and fuzzy logic

Within companies, production is directly concerned with the manufacturing schedule, but other services like sales, maintenance, purchasing or workforce management should also have an influence on this schedule. These services often have together a hierarchical relationship, i.e. the leading function (most of the time sales or production) generates constraints defining the framework within which the other functions have to satisfy their own objectives. We show how the multi-agent paradigm, often used in scheduling for its ability to distribute decision-making, can also provide a framework for making several functions cooperate in the schedule performance. Production and maintenance have been chosen as an example: having common resources (the machines), their activities are actually often conflicting. We show how to use a fuzzy logic in order to model the temporal degrees of freedom of the two functions, and show that this approach may allow one to obtain a schedule that provides a better compromise between the satisfaction of the respective objectives of the two functions

Procedural Optimization Models for Multiobjective Flexible JSSP

The most challenging issues related to manufacturing efficiency occur if the jobs to be sched-uled are structurally different, if these jobs allow flexible routings on the equipments and mul-tiple objectives are required. This framework, called Multi-objective Flexible Job Shop Scheduling Problems (MOFJSSP), applicable to many real processes, has been less reported in the literature than the JSSP framework, which has been extensively formalized, modeled and analyzed from many perspectives. The MOFJSSP lie, as many other NP-hard problems, in a tedious place where the vast optimization theory meets the real world context. The paper brings to discussion the most optimization models suited to MOFJSSP and analyzes in detail the genetic algorithms and agent-based models as the most appropriate procedural models

Scheduling Algorithms: Challenges Towards Smart Manufacturing

Collecting, processing, analyzing, and driving knowledge from large-scale real-time data is now realized with the emergence of Artificial Intelligence (AI) and Deep Learning (DL). The breakthrough of Industry 4.0 lays a foundation for intelligent manufacturing. However, implementation challenges of scheduling algorithms in the context of smart manufacturing are not yet comprehensively studied. The purpose of this study is to show the scheduling No.s that need to be considered in the smart manufacturing paradigm. To attain this objective, the literature review is conducted in five stages using publish or perish tools from different sources such as Scopus, Pubmed, Crossref, and Google Scholar. As a result, the first contribution of this study is a critical analysis of existing production scheduling algorithms\u27 characteristics and limitations from the viewpoint of smart manufacturing. The other contribution is to suggest the best strategies for selecting scheduling algorithms in a real-world scenario

Working Notes from the 1992 AAAI Spring Symposium on Practical Approaches to Scheduling and Planning

The symposium presented issues involved in the development of scheduling systems that can deal with resource and time limitations. To qualify, a system must be implemented and tested to some degree on non-trivial problems (ideally, on real-world problems). However, a system need not be fully deployed to qualify. Systems that schedule actions in terms of metric time constraints typically represent and reason about an external numeric clock or calendar and can be contrasted with those systems that represent time purely symbolically. The following topics are discussed: integrating planning and scheduling; integrating symbolic goals and numerical utilities; managing uncertainty; incremental rescheduling; managing limited computation time; anytime scheduling and planning algorithms, systems; dependency analysis and schedule reuse; management of schedule and plan execution; and incorporation of discrete event techniques

A theoretical and computational basis for CATNETS

The main content of this report is the identification and definition of market mechanisms for Application Layer Networks (ALNs). On basis of the structured Market Engineering process, the work comprises the identification of requirements which adequate market mechanisms for ALNs have to fulfill. Subsequently, two mechanisms for each, the centralized and the decentralized case are described in this document. These build the theoretical foundation for the work within the following two years of the CATNETS project. --Grid Computing

Theoretical and Computational Basis for Economical Ressource Allocation in Application Layer Networks - Annual Report Year 1

This paper identifies and defines suitable market mechanisms for Application Layer Networks (ALNs). On basis of the structured Market Engineering process, the work comprises the identification of requirements which adequate market mechanisms for ALNs have to fulfill. Subsequently, two mechanisms for each, the centralized and the decentralized case are described in this document. --Grid Computing

Towards a distributed multi-agent framework for shared resources scheduling

Nowadays, manufacturers have to share some of their resources with partners due to the competitive economic environment. The management of the availability periods of shared resources causes a problem because it is achieved by the scheduling systems, which assume a local environ- ment where all resources are on the same site. Therefore, distributed scheduling with shared resources is an impor- tant research topic. In this communication, we introduce the architecture and behaviour of DSCEP framework (Dis- tributed, Supervisor, Customer, Environment, and Producer) under shared resources situation with disturbances. We are using a simple example of manufacturing system to illustrate the ability of DSCEP framework to solve the shared resources scheduling problem in complex systems

Decentralized aircraft landing scheduling at single runway non-controlled airports

The existing air transportation system is approaching a bottleneck because its dominant huband- spoke model results in a concentration of a large percentage of the air traffic at a few hub airports. Advanced technologies are greatly needed to enhance the transportation capabilities of the small airports in the U.S.A., and distribute the high volume of air traffic at the hub airports to those small airports, which are mostly non-controlled airports. Currently, two major focus areas of research are being pursued to achieve this objective. One focus concentrates on the development of tools to improve operations in the current Air Traffic Management system. A more long-term research effort focuses on the development of decentralized Air Traffic Management techniques. This dissertation takes the latter approach and seeks to analyze the degree of decentralization for scheduling aircraft landings in the dynamic operational environment at single runway noncontrolled airports. Moreover, it explores the feasibility and capability of scheduling aircraft landings within uninterrupted free-flight environment in which there is no existence of Air Traffic Control (ATC). First, it addresses the approach of developing static optimization algorithms for scheduling aircraft landings and, thus, analyzes the capability of automated aircraft landing scheduling at single runway non-controlled airports. Then, it provides detailed description of the implementation of a distributed Air Traffic Management (ATM) system that achieves decentralized aircraft landing scheduling with acceptable performance whereas a solution to the distributed coordination issues is presented. Finally real-time Monte Carlo flight simulations of multi-aircraft landing scenarios are conducted to evaluate the static and dynamic performance of the aircraft landing scheduling algorithms and operation concepts introduced. Results presented in the dissertation demonstrate that decentralized aircraft landing scheduling at single runway non-controlled airports can be achieved. It is shown from the flight simulations that reasonable performance of decentralized aircraft landing scheduling is achieved with successful integration of publisher/subscriber communication scheme and aircraft landing scheduling model. The extension from the non-controlled airport application to controlled airport case is expected with suitable amendment, where the reliance on centralized air traffic management can be reduced gradually in favor of a decentralized management to provide more airspace capacity, flight flexibility, and increase operation robustness