Effective preventive healthcare services have a significant role in reducing fatality and medical expenses in all human societies and the level of accessibility of customers to these services can be considered as a measure of their efficiency and effectiveness. The main purpose of this paper is to develop a service network design model of preventive healthcare facilities with the principal obje...

Abstract In this paper, we study the recently introduced time-constrained maximal covering routing problem. problem, are given a central depot, set of facilities, and customers. Each customer is associated with subset facilities which can cover it. A feasible solution consists k Hamiltonian cycles on subsets depot. cycle must contain depot respect distance limit. The goal to maximize number cus...

In this paper, a model is presented to locate ambulances, considering backup facility (to increase reliability) and the restriction of ambulance capacity. This model is designed for emergencies. In this model the covered demand for each demand point depends on the number of coverage times and the amount of demand. The demand amount and ambulance coverage radius are considered...

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...

This paper provides a framework in order to incorporate reliability issue as a sign of disruption in distribution systems and partial covering theory as a response to limitation in coverage radios and economical preferences, simultaneously into the traditional literatures of capacitated facility location problems. As a result we develop a bi-objective model based on the discrete scenarios for e...

The Constructive Genetic Algorithm (CGA) was proposed by Lorena and Furtado [6], as an alternative to the traditional GAs approach. Particularly the CGA directly evaluates schemata, works with a dynamic population size, performs mutation in complete structures, and uses heuristics in schemata and/or structure representation. The schemata are evaluated and can be added to the population if they ...