The generalized traveling salesman problem (GTSP) is an extension of the classical
traveling salesman problem (TSP) and it is among the most researched combinatorial …

Nature has been considered as an inspiration of several recent meta-heuristic algorithms.
This paper firstly studies and mimics the behavior of Scottish red deer in order to develop a …

The deep convolutional neural network (CNN) is the state-of-the-art solution for large-scale
visual recognition. Following some basic principles such as increasing network depth and …

The quick growth of urbanization and population, as well as the transformation of industrial
and materials, have pushed the management of municipal solid waste into a crisis …

Ensemble learning has gained success in machine learning with major advantages over
other learning methods. Bagging is a prominent ensemble learning method that creates …

Abstract Home Health Care Supply Chain (HHCSC) is an interesting and widespread topic
in developed countries due to an aging population's care. Home care services aim to …

Growing environmental concerns and social legislations enforce decision makers to design
their supply chains considering environmental and social impacts as well as economical …

Network design problems (NDP) consist of identifying an optimal subgraph of a graph,
subject to side constraints. In generalized NDP, the vertex set is partitioned into clusters and …

Abstract Generally, in Home Health Care (HHC) logistics, caregivers which are started from
a pharmacy are scheduled and routed to do different care services at patients' home. At the …

Recently, supply chain network design has been a demanding question and attracted great
interest in a wide range of fields, including the medical industry. The heart of the entire …