Sharif Digital Repository

In this study, the authors optimise the outage probability of amplify and forward incremental relaying (IR) scheme using two different power allocation methods in the presence of channel estimation errors. The authors find the outage probability of IR scheme and minimise it subject to traditional power (TP) constraint in which the sum of nodes' powers is fixed and outage-dependent power (ODP) constraint which is compatible with the physical concept of IR and takes into account the quality of the direct path in the optimisation problem. The authors provide closed-form expressions to allocate power to pilot and data symbols of both the source and the relay. Although, their analysis uses high... 

This paper studies the statistical properties of the signal-to-noise ratio (SNR) of the dual-hop relaying link in a cooperative wireless communication system in the presence of channel estimation errors for fixed-gain (FG) and variable-gain (VG) relays. The SNR expression is derived and three different analytical approaches with different simplifying assumptions are proposed to obtain the probability distribution function of the SNR and the outage probability in each mode. All but one approach result in closed-form expressions for the outage probability. The simplest approach in each mode has been used to find an optimum power allocation scheme for pilot and data symbols transmission at the... 

The growing rate of population and technological advancement have led to an increase in natural resource consumption, which has caused irreparable damage to the environment. The implementation of green supply chain management is one of the most effective ways to deal with environmental degradation. Therefore, in this paper, a bi-objective mixed integer linear programming model is developed to design a green supply chain network. In the proposed model, the possibility of customer storage, being faced with shortage, locating of distribution centres, green vehicle routing problem, split delivery, multi-depot vehicle routing problem (VRP), capacitated VRP, and uncertainty in demands will be... 

Supplier selection is an important and challenging problem in sustainable supply chain management. We propose a dynamic decision support system (DSS) for sustainable supplier selection in circular supply chains. Unlike the linear take-make-waste-dispose production systems, circular supply chains are nonlinear make-waste-recycle production systems with zero-waste vision. The proposed DSS allows users to customize and weight their economic, social, and circular criteria with a fuzzy best-worst method (BWM) and select the most suitable supplier with the fuzzy inference system (FIS). Machine learning is used to maintain and synthesize the criteria scores for the suppliers after each supplier... 

Supplier selection is an important and challenging problem in sustainable supply chain management. We propose a dynamic decision support system (DSS) for sustainable supplier selection in circular supply chains. Unlike the linear take-make-waste-dispose production systems, circular supply chains are nonlinear make-waste-recycle production systems with zero-waste vision. The proposed DSS allows users to customize and weight their economic, social, and circular criteria with a fuzzy best-worst method (BWM) and select the most suitable supplier with the fuzzy inference system (FIS). Machine learning is used to maintain and synthesize the criteria scores for the suppliers after each supplier... 

Machine learning algorithms often suffer from good generalization in testing domains especially when the training (source) and test (target) domains do not have similar distributions. To address this problem, several domain adaptation techniques have been proposed to improve the performance of the learning algorithms when they face accuracy degradation caused by the domain shift problem. In this paper, we focus on the non-homogeneous distributed target domains and propose a new latent subdomain discovery model to divide the target domain into subdomains while adapting them. It is expected that applying adaptation on subdomains increase the rate of detection in comparing with the situation... 

In the eld of supply chain, selecting a suitable green supplier could signi cantly help us decrease the cost and risks of the operations and increase the quality of green supply. This paper develops an integrated two-stage approach based on Fuzzy Analytic Hierarchy Process (FAHP) and multi-objective mixed-integer linear programming to select suppliers and allocate order in the green supply chain. In the rst stage, suppliers are evaluated using FAHP method and in the second stage, a multi-product multi-period supply chain is developed considering green location-routing problem, discounting, and time window under uncertainty. Then, a fuzzy solution approach is applied to solve the proposed... 

The increasing level of customer awareness and application of environmental laws by governments, on the one hand, and the increasing number of competitors, on the other hand, has obliged industry owners to include green activities in the design of the supply chain network. Green activities include any type of action that reduces environmental degradation. Hence, this study seeks to develop a bi-objective, mixed integer linear programming (MILP) model for designing a green supply chain network. In the proposed model, the minimisation of costs and detrimental environmental effects are discussed. LP metric method is used to solve the bi-objective model and the proposed model is run by using...