An enterprise resource planning (ERP) software is needed for industries and companies that want to develop in future. Many of the manufactures and companies have a problem with ERP software selection. An inappropriate selection process can affect both the implementation and the performance of the company significantly. Although several models are proposed to solve this problem many of them did n...

Models that aim to optimize the design of supply chain networks have gained more interest in the supply chain literature. Mixed-integer linear programming and discrete-event simulation are widely used for such an optimization problem. We present a hybrid approach to support decisions for supply chain network design using a combination of analytical and discrete-event simulation models. The prop...

In this paper we present a robust hybrid motion/force controller for rigid robot manipulators. The main contribution of this paper is that the proposed hybrid control system is able to accomplish motion objectives in free directions and force objectives in constrained directions under parametric uncertainty both in robot dynamics and stiffness constraint constant. Also, the given scheme is prov...

Numerical induction models are considered in this report to be models that aggregate lower-level information into higher-level measures for decision making. Various forms of uncertainty may be present in such models including hybrid uncertainties within the information elements being aggregated. After a review of some existing approaches for representing higher-order uncertainty in information,...

Coordination of operations with spatially and temporally shared resources, such as route segments, fixes, and runways, improves the efficiency of terminal airspace management. Problems in this category are, in general, computationally difficult compared to conventional scheduling problems. This paper presents a fast time algorithm formulation using a non-dominated sorting genetic algorithm (NSG...

This paper presents an efficient state estimation algorithm for hybrid systems based on a least-squares Interacting Multiple-Model setup. The proposed algorithm is shown to be computationally efficient when compared with the Moving Horizon Estimaton algorithm that is a brute force optimization algorithm for simultaneous discrete mode and continuous state estimation of a hybrid system. The main ...

Over the past decade micro and nanofluidics emerged as vital tools in the ongoing drive towards the development of nano-scale analysis and manufacturing systems. Accurate numerical modelling of the phenomena involved at these scales is essential in order to speed up the industrial design process for nanotechnology. However a parameter often ignored in hybrid simulations is the uncertainty level...

s: In this paper, we define the portfolio return as fuzzy average yield and risk as hybrid-entropy and variance to deal with the portfolio selection problem with both random uncertainty and fuzzy uncertainty, and propose a mean-variance hybrid-entropy model (MVHEM). A multi-objective genetic algorithm named Non-dominated Sorting Genetic Algorithm II (NSGA-II) is introduced to solve the model. W...

Ships play the major role in bulk transportation and they need their special energy system. This paper proposes a stochastic programing method for optimal sizing of a hybrid ship power system with energy storage system (ESS), photovoltaic power (PV) and diesel generator. To account for uncertainties, in this study a two-stage stochastic mixed-integer non-linear programing is used to model the o...

An essential requirement for a comprehensive use of hybrid data is the consideration and processing of its uncertainty. Erroneous interpretations of analyses can be avoided if uncertainty is integrated as a mandatory component, stored and considered in all operations. In this contribution, a probabilistic approach is presented for modelling geometric and thematic uncertainty. By means of a floo...