Strong collaboration in supply chain at B2B market may improve operational and financial performance of both suppliers clients. Need for benefits realization is especially actual supplying manufacturers with huge investments inventory as well high ordering carrying costs. Traditional stock level optimization models rely on historic data which makes them inefficient when if influenced by changin...

Recently there has been an increasing interest in primal-dual methods for model predictive control (MPC), which require minimizing the (augmented) Lagrangian at each iteration. We propose a novel first order method, termed proportional-integral projected gradient MPC where underlying finite horizon optimal problem both state and input constraints. Instead of Lagrangian, iteration our method onl...

Predictive modeling of habitat distribution of range plant species and identification of their potential habitats play important roles in the restoration of disturbed rangelands. This study aimed to predict the geographical distribution of Artemisia sieberi and find the influential variables in the distribution of A. sieberi in the desert rangelands of central Iran. Maps of environmental variab...

This paper introduces a procedure for controlling autonomous vehicles entering roundabouts. The aim of the centralized controller is to define velocity profile each vehicle by which collisions can be avoided and traveling times minimized. To achieve these performances, model predictive control introduced based on solution an analytical calculation spent in roundabout designing vehicles’ profile...

This paper presents a novel distributed active set method for model predictive control of linear systems. The combines primal strategy with decentralized conjugate gradient to solve convex quadratic programs. An advantage the proposed compared existing algorithms is feasibility iterates. Numerical results show that can compete alternating direction multipliers in terms communication requirement...