This paper considers a multi-periodic multi-shift call center staffing problem with two types of jobs: calls and emails. The arrival rate of calls is random and the workforce presents some flexibility: the agents can be affected to one job type in real-time. At each period of the day, a service quality constraint limits the waiting time for a call. The staffing problem is modeled as a newsboy-t...

Modeling and simulation efforts continue to expand in areas where they have been used for some time, and they are also beginning to be used in new application areas. Modeling and simulation have been heavily used in risk assessment for high-consequence systems, such as nuclear power reactors, underground storage of radioactive wastes, and the nuclear weapon stockpile. For complex engineered or ...

In model-based fault diagnosis for dynamic systems with uncertain parameters, an envelope of all fault-free behaviors can be determined from the model and used as a reference for detecting faults. We demonstrate here a method for generating an envelope that is rigorously guaranteed to be complete, but without significant overestimation. The method is based on an interval approach, but uses Tayl...

Linear Programming (LP) remains the workhorse of applied optimization, having openloop process applications such as production planning, inventory scheduling and closedloop applications such as Real-time optimization and the steady-state determination at each execution of a Model Predictive Controller (MPC). This paper presents new methods for monitoring performance (estimating the degradation ...

Usually when determining parameters with an inverse method, it is assumed that parameters or properties, other than those being sought, are known exactly. When such known parameters are uncertain, the inverse solution can be very sensitive to the degree of uncertainty. The stochastic regularization method can be modi ed to reduce this sensitivity. This paper presents such a modi cation. In addi...

Algorithms for full 3D robotic visual tracking of moving targets whose motion is 3D and consists of translational and rotational components are presented. The objective of the system is to track selected features on moving objects and to place their projections on the image plane at desired positions by appropriate camera motion. The most important characteristics of the proposed algorithms are...

Although we usually would like to work with exact systems, most of the real world systems are nonlinear with uncertain parameters. In this paper, we propose AVK (A.V. Kamyad) approach to solve nonlinear problems with uncertain parameters (NPUP). This approach substitutes the original nonlinear system with an equivalent nonlinear programming (NLP) problem. Using this approach, we found an optima...

This paper deals with uncertain parabolic fluid flow problem where the uncertainty occurs due to the initial conditions and parameters involved in the system. Uncertain values are considered as fuzzy and these are handled through a recently developed method. Here the concepts of fuzzy numbers are combined with Finite Difference Method (FDM) and then Fuzzy Finite Difference Method (FFDM) has bee...

In the context of possibilistic decision making, this work deals with biological design problems particularly important in the near future when it will be possible to produce biological entities and synthetic organisms for pharmacological and medical usage. The biological systems is investigated in terms of performances or main key features of the system. The analysis of the biological system i...

We outline the use of a data-free inference procedure for estimation of uncertain model parameters for a chemical model of methane-air ignition. The method involves a nested pair of Markov chains, exploring both the data and parametric spaces, to discover a pooled joint posterior consistent with available information. We describe the highlights of the method, and detail its particular implement...