Abstract: In this paper, the single-depot capacitated
location-routing problem under uncertainty is presented. The
problem aims to find the optimal location of a single depot and
the routing of vehicles to serve the customers when the parameters
may change under different circumstances. This problem has many
applications, especially in the area of supply chain management and
distribution systems. To get closer to real-world situations, travel time
of vehicles, the fixed cost of vehicles usage and customers’ demand
are considered as a source of uncertainty. A combined approach
including robust optimization and stochastic programming was
presented to deal with the uncertainty in the problem at hand. For
this purpose, a mixed integer programming model is developed and
a heuristic algorithm based on Variable Neighborhood Search(VNS)
is presented to solve the model. Finally, the computational results
are presented and future research directions are discussed.
Abstract: With increasing life expectancy in developed countries, the role of home care services is highlighted by both academia and industrial contributors in Home Health Care Supply Chain (HHCSC) companies. The main decisions in such supply chain systems are the location of pharmacies, the allocation of patients to these pharmacies and also the routing and scheduling decisions of nurses to visit their patients. In this study, for the first time, an integrated model is proposed to consist of all preliminary and necessary decisions in these companies, namely, location-allocation-routing model. This model is a type of NP-hard one. Therefore, an Imperialist Competitive Algorithm (ICA) is utilized to solve the model, especially in large sizes. Results confirm the efficiency of the developed model for HHCSC companies as well as the performance of employed ICA.