Abstract: Bi-level programming, a tool for modeling decentralized decisions, consists of the objective(s) of the leader at its first level and that is of the follower at the second level. Three level programming results when second level is itself a bi-level programming. By extending this idea it is possible to define multi-level programs with any number of levels. Supply chain planning problem...

in this study, a new stochastic model is proposed to deal with a multi-product, multi-period, multi-stage, multi-site production and transportation supply chain planning problem under demand uncertainty. a two-stage stochastic linear programming approach is used to maximize the expected profit. decisions such as the production amount, the inventory level of finished and semi-finished product, t...

a few of the presented soil behavior models are capable of predicting the triggering and post liquefaction and also shear band mechanism through the soil media. the assessment of earth-dam body behavior as a soil structure made of cohesive soil in core and non-cohesive soil as the core supports, including water interaction at upstream through earthquake upon a multi-line constitutive equations ...

this paper develops a single-vendor single-retailer supply chain for multi-product. the proposed model is based on vendor managed inventory (vmi) approach and vendor uses the retailer's data for better decision making. number of orders and available capital are the constraints of the model. in this system, shortages are backordered; therefore, the vendor’s warehouse capacity is another limitati...

agent technology is an emerging and promising research area in software technology, which increasingly contributes to the development of value-added information systems for large healthcare organizations due to its capability to automatically modify themselves in response to changes in their operating environment. multi agent system (mas) approach is the construction of a complex system as a se...

This article deals with the issues associated with developing a new design methodology for the nonlinear model-predictive control (MPC) of a chemical plant. A combination of multiple neural networks is selected and used to model a nonlinear multi-input multi-output (MIMO) process with time delays.  An optimization procedure for a neural MPC algorithm based on this model is then developed. T...