The hub location–allocation problem under uncertainty is a real-world task arising in the areas such as public and freight transportation and telecommunication systems. In many applications, the demand is considered as inexact because of the forecasting inaccuracies or human’s unpredictability. This study addresses the robust uncapacitated multiple allocation hub location problem with a set of ...

Environmental crisis and shortage of fossil fuels make Electric Vehicles (EVs) alternatives for conventional vehicles. With growing numbers of EVs, the coordinated charging is necessary to prevent problems such as large peaks and power losses for grid and to minimize charging costs of EVs for EV owners. Therefore, this paper proposes an optimal charging schedule based on Dynamic Programming (DP...

In this paper, a bi-objective model is proposed for designing a pre-positioning network of pharmaceutical supplies considering their limited shelf-life. The presented model aims to consider both cost efficiency and responsiveness by minimization of total cost and the maximum amount of unmet demand under uncertainties in demand and supply sides’ data. Moreover, for effective distribution of reli...

In this article, a finite horizon, multi product and multi period economic order quantity like seasonal items is considered where demand rate is deterministic and known but variable in each period. The order quantities of items come in batch sizes and the end of the period order quantity and, consequently, demand of customers are zero. In addition, storage space is constrained and the problem...

A new procedure for learning cost-sensitive SVM classifiers is proposed. The SVM hinge loss is extended to the cost sensitive setting, and the cost-sensitive SVM is derived as the minimizer of the associated risk. The extension of the hinge loss draws on recent connections between risk minimization and probability elicitation. These connections are generalized to costsensitive classification, i...

Small-scale dairy farming in Bangladesh is constrained mostly due to acute shortage, high price and seasonal fluctuation of energy and protein supplements. Poor economic conditions of dairy farmers do not allow them to purchase adequate conventional energy and protein supplements. Locally available non-conventional energy and protein sources can be used as alternatives, cheaper than conventiona...

in this paper, we introduce a methodology for safety stock placement in supply chain. the problem has two objectives: minimization of good's delivery time and inventory cost. because the problem belongs to np-hard category, we develop a proper simulated annealing algorithm (sa) for solve the proposed methodology in large scaled problem. for verify the performance and efficiency of the meth...

Natural disasters and crisis are inevitable and each year impose destructive effects on human as injuries and damage to property. In natural  disasters and after the outbreak of the crisis, demand for logistical goods and services increase. Effective distribution of emergency aid could have a significant role in minimizing the damage and fatal accident. In this study, a three-level relief chain...

Using distributed generations (DGs) with optimal scheduling and optimal distribution feeder reconfiguration (DFR) are two aspects that can improve efficiency as well as technical and economic features of microgrids (MGs). This work presents a stochastic copula scenario-based framework to jointly carry out optimal scheduling of DGs and DFR. This framework takes into account non-dispatchable and ...

Abstract. Any intelligent system performing evidence-based decision making under time pressure must negotiate a speed-accuracy trade-off. In computer science and engineering, this is typically modeled as minimizing a Bayes-risk functional that is a linear combination of expected decision delay and expected terminal decision loss. In neuroscience and psychology, however, it is often modeled as m...