drought is random and nonlinear phenomenon and using linear stochastic models, nonlinear artificial neural network and hybrid models is advantaged for drought forecasting. this paper presents the performances of autoregressive integrated moving average (arima), direct multi-step neural network (dmsnn), recursive multi-step neural network (rmsnn), hybrid stochastic neural network of directive ap...

emission trading is one of the famous mechanisms under kyoto protocol to control environmental pollution. the aim of this paper is to design a strategic supply chain network under emission trading scheme with inclusion of stochastic parameters and budget limitation. demand and price of carbon credits are considered as the important stochastic parameters influencing the supply chain network. in ...

Supply chain network design in perishable product has become a challenging task due to its short life time, spoilage of product in degradation nature and stochastic market demand. This paper focused on designing and optimizing model for perishable product in stochastic demand, which comprises multiple levels from producer, local collector, wholesaler and retailers. The ultimate goal is to optim...

the hub location decision is a long term investment and any changes in it take considerable time and money. in real situations, some parameters are uncertain hence, deterministic models cannot be more efficient. the ability of two-stage stochastic programming is to make a long-term decision by considering effects of it in short term decisions simultaneously. in the two-stage stochastic programm...

Due to the importance of longest path analysis in networks of queues, we develop an analytical method for computing the steady-state distribution function of longest path in acyclic networks of queues. We assume the network consists of a number of queuing systems and each one has either one or infinite servers. The distribution function of service time is assumed to be exponential or Erlang. Fu...

design of a logistics network in proper way provides a proper platform for efficient and effective supply chain management. this paper studies a multi-period, multi echelon and multi-product integrated forward-reverse logistics network under uncertainty. first, an efficient complex mixed-integer linear programming (milp) model by considering some real-world assumptions is developed for the inte...

In this paper, a comprehensive mathematical model for designing an electric power supply chain network via considering preventive maintenance under risk of network failures is proposed. The risk of capacity disruption of the distribution network is handled via using a two-stage stochastic programming as a framework for modeling the optimization problem. An applied method of planning for the net...

this research provides an optimization tool for use by supply chain managers in the design and operation of manufacturing- distribution networks under uncertain demand conditions. the problem under consideration consists of determining the supply chain infrastructure; raw material purchases, shipments, and inventories; and finished product production quantities, inventories, and shipments neede...

in this paper a network comprising alternative branching nodes with probabilistic outcomes is considered. in other words, network nodes are probabilistic with exclusive-or receiver and exclusive-or emitter. first, an analytical approach is proposed to simplify the structure of network. then, it is assumed that the duration of activities is positive trapezoidal fuzzy number (tfn). this paper com...

the problem we investigate deals with the optimal assignment of resources to the activities of a stochastic project network. we seek to minimize the expected cost of the project include sum of resource utilization costs and lateness costs. we assume that the work content required by the activities follows an exponential distribution. the decision variables of the model are the allocated resourc...