We consider the single-machine scheduling problem to minimize the weighted sum of completion times under precedence constraints. In a series of recent papers, it was established that this scheduling problem is a special case of minimum weighted vertex cover. In this paper, we show that the vertex cover graph associated with the scheduling problem is exactly the graph of incomparable pairs defin...

Machine scheduling is to assign a group of jobs to a set of machines in an efficient strategy, such that some objectives such as minimizing the makespan time are satisfied under some constraints. Considering the human uncertainty in operations, this paper assumes the processing times of the jobs are uncertain variables, and proposes an uncertain goal programming model for the machine scheduling...

This paper deals with electromagnetic design and 2-D (two-dimensional) magnetic field analysis of novel low force ripple linear switched reluctance (LSR) motor. The configuration that has been presented here has a higher number of rotor poles than stator poles, and the purpose of this configuration is to improve the force ripple, which is the weak point of LSRMs. In order to illustrate the ...

In this chapter we explain briefly the fundamentals of the interactive scores formalism. Then we develop a solution for implementing the ECO machine by mixing petri nets and constraints propagation. We also present another solution for implementing the ECO machine using concurrent constraint programming. Finally, we present an extension of interactive score with conditional branching.

Our research focuses on the identification of word usage constraints from large text corpora. Such constraints are important for natural language systems, both for the problem of selecting vocabulary for language generation and for disambiguating lexical meaning in interpretation. The first stage of our research involves the development of systems that can automatically extract such constraints...

A new Lagrangian relaxation (LR) approach is developed for job shop scheduling problems. In the approach, operation precedence constraints rather than machine capacity constraints are relaxed. The relaxed problem is decomposed into single or parallel machine scheduling subproblems. These subproblems, which are NP-complete in general, are approximately solved by using fast heuristic algorithms. ...

Classical supervised learning assumes that training data is representative of the data expected to be observed in the future. This assumption is clearly violated when an intelligent adversary actively tries to deceive the learner by generating instances very different from those previously seen. The literature on adversarial machine learning aims to address this problem, but often assumes const...

This paper deals with the optimal control of interior permanent magnet synchronous machine (IPM) in the integrated starter-generator (ISG) application. IPM designed for flux-weakening operations are able to realise high performances. Nevertheless, the ISG environment imposes lots of constraints which must be taken into account in an appropriate control. After a presentation of machine design, I...

Efficient learning of an appropriate distance metric is an increasingly important problem in machine learning. However, current methods are limited by scalability issues or are unsuited to use with general similarity/dissimilarity constraints. In this paper, we propose an efficient metric learning method based on the max-margin framework with pairwise constraints that has a strong generalizatio...

Synthesizing specifications for real time applications that involve distributed communication protocol entities from a service specification, which is modeled in the UML state machine with composite states, is a time-consuming and labor-intensive task. Existing synthesis techniques for UML-based service specifications do not account for timing constrains and, therefore, cannot be used in real t...