Previous pandemics in 1918, 1957, 1968, and the ongoing COVID-19 pandemic have provided sufficient evidence of health concerns caused by influenza pandemics. The existing care system is overwhelmed surging demand susceptible infected individuals due to outbreak. It crucial identify isolate prevent spread. Thus, a mixed-integer linear programming model proposed this study for location-allocation...

This paper proposes a bi-objective model for the facility location problem under a congestion system. The idea of the model is motivated by applications of locating servers in bank automated teller machines (ATMS), communication networks, and so on. This model can be specifically considered for situations in which fixed service facilities are congested by stochastic demand within queueing frame...

Our study is concerned with the development of an Emergency Medical Services (EMS) ambulance location and allocation model called the Time-based Ambulance Zoning Optimization Model (TAZ_OPT). This paper presents the framework of the study. The model is formulated using the goal programming (GP), where the goals are to determine the satellite locations of ambulances and the number of ambulances ...

Providing blood with high quality at the lowest cost and shortest time is main challenge of supply chain management. This paper presents a new model for designing dynamic three level incorporating issues. The proposed intends to locate facilities, determine best strategy allocation by minimizing both maximizing customer satisfaction based on delivery. In order deal consideration real world, int...

Location-allocation problems arise in several contexts, including supply chain and data mining. In its most common interpretation, the basic problem consists of optimally locating facilities and allocating customers to facilities so as to minimize the total cost. The standard approach to solving location-allocation problems is to model alternative location sites and customers as discrete entiti...

A fuzzy queuing coherent hierarchical location-allocation model is developed for congested systems. The parameters of the model are approximately evaluated and stated as fuzzy-numbers. The coverage of demand nodes is also considered in an approximate manner and is stated by the degree of membership. Using the queuing theory and fuzzy conditions, a coherent hierarchical model is developed for th...

The Maximal Covering Location Problem (MCLP) maximizes the population that has a facility within a maximum travel distance or time. Numerous extensions have been proposed to enhance its applicability, like the probabilistic model for the maximum covering locationallocation with constraint in waiting time or queue length for congested systems, with one or more servers per service center. This pa...

In this paper we address the issue of locating hierarchical facilities in the presence of congestion. Two hierarchical models are presented, where lower level servers attend requests first, and then, some of the served customers are referred to higher level servers. In the first model, the objective is to find the minimum number of servers and their locations that will cover a given region with...

This research develops a clustering-based location-allocation method to the Capacitated Facility Location Problem (CFLP), which provides an approximate optimal solution to determine the location and coverage of a set of facilities to serve the demands of a large number of locations. The allocation is constrained by facility capacities – different facilities may have different capacities and the...