Extended Forms of Coverage

Abstract

Industrial and public sector planning is often complex. Example contexts include making a city safer or designing a manufacturing supply chain. Models can assist in the design of such systems by tracking the major components and generating top performing solutions. Some of the best planning models are simple, easy to understand, and easily applied and solved. At a minimum, a model must capture the main essence of the problem. Two examples of such planning models are the LSCP (location set covering problem) and MCLP (maximal covering location problem) described in Chap. 2. Because they are so simple and powerful as planning models, they have been used in many different ways, from biological reserve design (Underhill 1994) to advertising (Dwyer and Evans 1981) to prosthetic teeth coloring (Cocking et al. 2009) to health clinic location (Bennett et al. 1982). There are, however, a number of elements and conditions that are not captured exactly using these two basic constructs of complete coverage or maximal coverage. Because of this, researchers have proposed a wide variety of extended model forms to better reflect specific elements of a given problem. In this chapter we present some of the work, including multi-service, hierarchical, and multi-factor issues, in coverage modeling.