Technical Sessions A6 - E6
SESSION A6: GOTHA: Mathematical and Approximation Models for Scheduling Problems
 Branch and Price
for a Reliability Oriented DARP Model
Alain Quilliot, Samuel Deleplanque and Benoit Bernay
We deal here with the static version of decisional model related to real time monitoring of a DARP (Dial and Ride) system which involves, on a closed industrial site, small electrical autonomous vehicles. Because of technological issues, we focus on reliability, and propose a model which assigns requests to vehicles while minimizing Load/Unload transactions. We study this model through both a Branch/Price approach, which provides us with benchmarks, and insertion based heuristics, well-fitted to dynamic contexts.
algorithm for constrained coupled-tasks scheduling problem
Gilles Simonin, Benoit Darties, Jean-Claude Konig and
We tackle the makespan minimization coupled-tasks problem in presence of compatibility constraints. In particular, we focus on stretched coupled-tasks, i.e. coupled-tasks having the same sub-tasks execution time and idle time duration. In such context, we propose some complexity results according to several parameters and we design an efficient polynomial-time approximation algorithm.
 An Improved
Approximation Algorithm for the Ancient Scheduling Problem
Eugene Levner and Amir Elalouf
The aim of this paper is to develop an improved polynomial-time approximation algorithm belonging to the family of the fully polynomial time approximation schemes (FPTAS), for an ancient scheduling problem with deadlines. The algorithm permits to answer a question posed more than three decades ago in Gens & Levner (1981): “Can an epsilon-approximation algorithm be found for the minimization version of the job-sequencing-with-deadlines problem running with the same complexity as the algorithms for the maximization form of the problem?” The new algorithm provides the positive answer.
 Branch and Price
with Constraint propagation for Resource Constrained
Project Scheduling Problem
Aziz Moukrim, Alain Quilliot and Hélène Toussaint
This paper describes an efficient exact algorithm to solve the Resource Constrained Project Scheduling Problem(RCPSP). We propose an original and efficient branch and price procedure which involves minimal interval order enumeration as well as constraint propagation and which is implemented with the help of the generic SCIP software. We perform tests on the famous PSPLIB instances which provide very satisfactory results.
SESSION B6: Prediction, Forecasting and Optimization
 Single-item lot
sizing problem with carbon emission under the cap-and-trade policy
Ayse Akbalik and Christophe Rapine
We study the integration of the carbon emission constraint into the single item uncapacitated lot sizing problem (ULSP) under the cap-and-trade policy. Besides a limitation on the total carbon emitted through the production and storage activities over the entire hoziron, the cap-and-trade policy allows the firm to buy and to sell carbon units in case of need or surplus. In addition to the classical lot sizing costs (setup cost, unit production and unit holding costs) we take into account a cost of buying and a cost of selling carbon units. The speculative trades are not allowed by assuming stationary prices both for selling and buying activities. With an unlimited budget assumption, we show that the problem is equivalent to the classical ULSP which is polynomially solvable. We study two budget constraints and we show the problem to be NP-hard in the ordinary sense under a limited budget assumption using a recent result in Helmrich et al., 2012. We also show that both problems under different budget constraints and carbon trade costs can be reduced to the problem studied in Helmrich et al., 2012.
 Decentralized versus
Centralized Performances in the Case of Stackelberg Game between
a Customer and two Suppliers
Ibtissem Ernez Gahbiche, Khaled Hadj Youssef, Abdelwaheb Dogui
and Zied Jemai
The present paper considers a supply chain which consists of a customer and two capacitated suppliers. The customer receives the proposition of a new product procurement and seeks to allocate demand volume to suppliers in a manner to maximize his profit. Suppliers employ base stock policies for inventory replenishment. Each supplier chooses a base stock level which maximizes his profit. In addition, we let each member accept or refuse the new product proposal according to its profitability. We investigate the Stackelberg game where the customer dominates the supply chain. By comparing the resulting system performances with the corresponding centralized one, we show that the inefficiency of the Stackelberg game may reach more than 80% in quite a lot of cases. We underline the benefit of cooperation, and provide some profit allocation arrangements that lead to better players' profits.
 SVDD: A proposal for
automated credit rating prediction
Claude Gangolf, Robert Dochow, Günter Schmidt and Thomas
Credit rating prediction using clustering algorithms has become more and more important in the financial literature. Expanding the ideas of [Kim05] and [Lee07], we propose an approach to generate models for credit rating prediction based on support vector domain description (SVDD) and linear regression (LR). The generated models imply the rating of sovereign and corporate bonds. Another advantage is that the rating models contain as many groups as rating grades exist, as given by rating agencies as S & P, Fitch and Moody's. Then our approach is formulated as a step-by-step procedure and all steps are illustrated by a small example.
 Optimal Search
with Bounded Daily Returns
The 'reservation price policy' of El-Yaniv (1998) is based on the assumption that asset prices are arbitrary drawn from a pair of upper an lower bounds, that is, m and M. By defining a set of constants the maximum interday price fluctuation can be bounded in order to reduce market volatility. Arbitrary price movements like a sudden drop from M to m are excluded. We present and analyze online conversion algorithms under bounded daily returns. Results show that an investor solely requires the a-priori information whether the price function is symmetric or not to choose the algorithm with the smallest competitive ratio.
SESSION C6: Control
 Cascaded Backstepping
Control of a Duocopter Including Disturbance Compensation by
Unscented Kalman Filtering
Thomas Meinlschmidt, Harald Aschemann and Saif Siddique Butt
A cascaded control strategy for an innovative Duo-copter test stand – a helicopter with two rotors combined with a guiding mechanism – is presented in this paper. The guiding mechanism consists of a rocker arm with a sliding carriage that enforces a planar workspace of the Duocopter. The Duocopter is connected to the carriage by a rotary joint and offers 3 degrees of freedom. The derived system model has similarities with a PVTOL and a planar model of a quadrocopter but involves
additional terms due to the guiding mechanism. In the paper, a model-based cascaded control strategy is proposed: the outer MIMO control loop is given by the inverted system model to control the horizontal and the vertical Duocopter position with a
nonlinear error dynamics derived from backstepping techniques. The rotation angle of the Duocopter is controlled in a linear inner control loop of high bandwidth. Due to uncertain system parameters and reasonable simplifications at the modelling of the test stand, the control structure is extended by an unscented Kalman filter. Thereby, an excellent tracking performance in vertical and horizontal direction can be achieved. The efficiency of the proposed control strategy is demonstrated by both simulations and experiments.
Flatness-Based Control of a Helicopter with Two Degrees of
Saif Siddique Butt, Robert Prabel and Harald Aschemann
In this paper, a multi-variable nonlinear control of a twin rotor aerodynamical system (TRAS) is presented. A control-oriented state-space model with four states is derived employing Lagrange’s equations. Using this system representa-tion, a multi-variable flatness-based control is designed for an accurate trajectory tracking concerning both the pitch angle characterising the vertical motion and the azimuth angle related to the horizontal motion. Due to unmeasurable states as well as disturbance torques affecting the pitch axis and the azimuth axis, a discrete-time Extended Kalman Filter (EKF) is employed and combined with a discrete-time implementation of the multi-variable flatness-based control. The effectiveness of the proposed control strategy is highlighted by experimental results from a test
rig that show an excellent tracking behaviour.
 A sufficient condition
on the robust monotonic convergence of uncertain 2-D
Zhifu Li, Yueming Hu and Qiwei Guo
This paper investigates the robust monotonic convergence of discrete uncertain two-dimensional (2-D) systems described by Roesser model. The robust monotonic convergence problem of the uncertain 2-D system is firstly converted to two H∞ disturbance attenuation problems of the traditional one-dimensional system. Then, the sufficient condition is derived for the robust monotonic convergence, which is given by two linear matrix inequalities (LMIs). Furthermore, it can be shown that either of the LMIs can also guarantee the Bounded-Input Bounded-Output (BIBO) stability of the uncertain 2-D system. Those observations would facilitate the analysis and synthesis of 2-D systems.
rejection based on a state feedback controller with
Asma Karoui, Kaouther Ben Taarit and Moufida Ksouri
The ”delay scheduling” procedure is a recent concept for the design of control system. ”Delay scheduling” strategy manipulates existing delays in the feedback as a control parameter which is increasing in order to recover stability. Indeed, the system should have many stable regions in the time delays domain. To do this, a recent procedure, Cluster Treatment of Characteristic Roots (CTCR) is deployed, allowing the exact determination of the complete picture of stable regions in time delays space. Starting from ”delay scheduling” and CTCR methods, the objective of the proposed approach is to track desired trajectories even in presence of time delay and static disturbances at the output of system.
SESSION D6: Identification and Control
Trajectory Planning by Big Bang-Big Crunch Algorithm
Sabri Yilmaz and Metin Gokasan
Path planning is an interesting topic which is affected by lots of variables, as: time, energy, torque and stability. In this study, a new method based on Big Bang-Big Crunch algorithm is proposed to find optimum values of the parameters of a path and a cost function in order to minimize applied torque and tracking error. For this purpose the mathematical model of the manipulator is derived with mainly used methods, Denavit- Hartenberg, Jacobian and Euler-Lagrange methods. By using classical robot modeling methods, Big Bang-Big Crunch algorithm searched for the optimum trajectory and found the optimum value of the cost function.
 Calculation of
All Gains Providing Time-Delay Independent Stability
Via Root Locus
Baris Samim Nesimioglu and Mehmet Turan Soylemez
In this paper, a simple root locus based graphical method is proposed to calculate all stabilizing (destabilizing) proportional controller set which provides time-delay independent stability for single input single output (SISO) systems with time-delay. In other words, for the gains belong to this set, if the delay-free system is stable, the time-delay system controlled with these gains remains stable, regardless of the value of the time-delay. Conversely, if the delay-free system is unstable, stability of the time-delay system is not affected by the value of the time delay; it remains unstable.
 On Trajectory
Tracking Control of the Inertia Wheel Pendulum
Javier Moreno-Valenzuela, Carlos Aguilar-Avelar and
Sergio A Puga
This paper deals with motion control of the inertia wheel pendulum. Specifically, we address a trajectory tracking problem. The proposed control algorithm is derived from feedback linearization, with the output of the system defined as the tracking error between a desired reference trajectory and the angular position of the inverted pendulum. The explicit expressions of the internal dynamics and zero-dynamics are obtained, where can be observed that the stability of the internal dynamics depends on the desired trajectory. Experimental evaluation of the proposed controller is presented, where we show that the trajectory tracking is accomplished for both upward and downward pendulum position, while the wheel velocity remains into the actuator constraints.
SESSION E6: Bio-inspired Systems for Chemical Component Control
 Application of
electronic nose to beer recognition using supervised
artificial neural networks
Maryam Siadat, Mahdi Ghasemi-Varnamkhasti, Seyed Saeid Mohtasebi
and Etienne Losson
Employment of electronic nose is drawing many attentions in brewery because of its unique capability in assessing multi-component analytes, which is largely feasible for traditional single-sensor devises. This study was aimed to recognize between alcoholic and non alcoholic beers by use of a MOS-based electronic nose system coupled with artificial neural networks (ANN) to evaluate the capability of the system for a binary discrimination. The PCA score plot of the two first principal components accounted for 78$\%$ of variance and clearly discrimination was observed. This observation was confirmed by ANN in such as way radial basis function (RBF) and Backpropagation (BP) showed satisfactory results to binary discrimination between two types of beer as 100 $\%$ of classification accuracy for both training and testing data sets. This result confirms the ability of the electronic nose to be used in future for other applications to beer evaluation in our project.
 Development of an
electronic equipment for the pre medical diagnose in the
progress of diabetic foot disease
Lorenzo Leija, Arturo Vera, Fátima Estela Lopez, Omar
Usiel Garcia, Josefina Gutierrez, Carlos Negreira and
This paper presents an instrument that uses electronic technologies to characterize the effects of diabetes by measuring the changes of the tissue physical characteristics, mainly in the foot. The instrument comprises 1) the measurement of glucose, 2) IR temperature measurement of the foot, 3) the differentiation of staining in areas of the foot, 4) the determination of the elasticity of vessels and foot tissues, 5) the determination of muscle impedance, 6) recording of the variation of the patient heart rate, 7) software that concentrates the digital information of the measured characteristics of the foot and a display to show the information to the physician. This article describes the results of temperature measurement on the sole of a foot, the patient result storage, a measurement method with RF impedance and the temperature of the foot taken with a commercial IR camera.
 Diagnosing lung
cancer in exhaled breath by using a chromatographic air
Jean-Baptiste Sanchez, Geoffrey Gregis, Igor Bezverkhyy,
Vanessa Fierro, Guy Weber, Alain Celzard, Franck Berger,
Jean-Pierre Bellat and Sebastien Schaefer
The analysis of volatile organic compounds (VOCs) that are linked to lung cancer is a very promising way in medical diagnostics because it is non-invasive and potentially inexpensive. In that sense, a silicon micro-analytical platform consisting of a three-dimensional micro-preconcentrator coupled to a silicon spiral GC micro column was built. A metal oxide-based gas sensor acted as a miniaturized gas detector. This system allowed selective detection of VOCs at the sub-ppm level. The aim of this study is to demonstrate the efficiency of this microsystem for the selective and sensitive detection of a group of VOCs characteristic of lung cancer in the gas phase.
 Application of
an Electronic Nose System Coupled with Artificial Neural
Network for Classification of Banana Samples During
Alireza Sanaeifar, Seyed Saeid Mohtasebi, Mahdi Ghasemi-Varnamkhasti
and Maryam Siadat
In this research, an electronic nose (e-nose) system was used to discriminate the volatile odors produced by banana during shelf-life process. A measurement system, equipped with six metal oxide semiconductor (MOS) sensors, was used to generate a recognition pattern of the volatile compounds of the banana samples. For pattern classification on data obtained from the sensor array of the electronic nose system, back-propagation multilayer perceptron (BP-MLP) neural network was used. By using BP-MLP technique, 97.33 and 94.44% classification successes were achieved for ripening and senescence period of banana respectively. Sensor array ability in classification of shelf-life stages using support vector machines (SVM) analysis was investigated which leaded to develop the application of a specific e-nose system by using the most effective sensors or ignoring the redundant sensors. According to the results, it is concluded that the electronic nose could be a useful tool for discriminating between shelf-life stages of banana.