An improved energy-efficient routing protocol based on Minimum Spanning Tree for Wireless Sensor Network

International audienc

Using Interval Petri Nets and timed automata for diagnosis of Discrete Event Systems (DES)

International audienceA discrete event system (DES) is a dynamic system that evolves in accordance with the abrupt occurrence, at possibly unknown irregular intervals, of physical events. Because of the special nature of these systems, different tools are currently used for their analysis, design and modeling. The main focus of this paper is the presentation of a new modeling approach of Discrete Event Systems. The proposed approach is based on hybrid model which combines Interval Constrained Petri Nets (ICPN) and Timed Automata. These tools allow us to evaluate, respectively, the quality variations and to manage the flow type disturbance. An example analysis illustrates our approac

A taxonomy for the flexible job shop scheduling problem

This chapter aims at developing a taxonomic framework to classify the studies on the flexible job shop scheduling problem (FJSP). The FJSP is a generalization of the classical job shop scheduling problem (JSP), which is one of the oldest NP-hard problems. Although various solution methodologies have been developed to obtain good solutions in reasonable time for FSJPs with different objective functions and constraints, no study which systematically reviews the FJSP literature has been encountered. In the proposed taxonomy, the type of study, type of problem, objective, methodology, data characteristics, and benchmarking are the main categories. In order to verify the proposed taxonomy, a variety of papers from the literature are classified. Using this classification, several inferences are drawn and gaps in the FJSP literature are specified. With the proposed taxonomy, the aim is to develop a framework for a broad view of the FJSP literature and construct a basis for future studies

A priority-based genetic algorithm for a flexible job shop scheduling problem

In this study, a genetic algorithm (GA) with priority-based representation is proposed for a flexible job shop scheduling problem (FJSP) which is one of the hardest operations research problems. Investigating the effect of the proposed representation schema on FJSP is the main contribution to the literature. The priority of each operation is represented by a gene on the chromosome which is used by a constructive algorithm performed for decoding. All active schedules, which constitute a subset of feasible schedules including the optimal, can be generated by the constructive algorithm. To obtain improved solutions, iterated local search (ILS) is applied to the chromosomes at the end of each reproduction process. The most widely used FJSP data sets generated in the literature are used for benchmarking and evaluating the performance of the proposed GA methodology. The computational results show that the proposed GA performed at the same level or better with respect to the makespan for some data sets when compared to the results from the literature.This research is partially supported by LATNA Laboratory, NRU HSE, RF government grant, ag. 11.G34.31.0057.info:eu-repo/semantics/publishedVersio