Professor Jacques A. Ferland, Department of Computer Science and Operations Research, University of Montreal, Montreal, Canada

Abstract

In post-emergency contexts in underdeveloped countries, one of the crucial challenges that rural hospitals face is maintaining a pharmacy with essential medications and supplies. There is significant negative humanitarian impact when hospitals do not have essential medications for treatable life-threatening diseases; hospitals also incur financial losses when too much medication is ordered and it expires. Moreover, the cost of transporting medications and providing on-site supervisor visits to remote hospitals is an extremely expensive endeavour. In some cases the transportation costs alone can surpass the cost of the medications. Using the province of Bandundu in DR Congo as a case study, we attempt to determine the feasibility (in terms of both problem complexity and potential savings) of a synchronized routing problem for medication deliveries and on-site supervisor visits. We propose a formulation that handles several novel requirements including the activity-wise synchronization, the precedence, and the two activity frequencies. We implement a novel cluster-first, route-second heuristic with a geospatially-enabled database to solve the problem. We also present a web-based tool to visualize the solutions on map. The preliminary results of the research suggest that a synchronized solution could allow rural hospitals to increase the accessibility of medical services to the populations with only a modest increase in transportation costs.

Biography

Jacques A. Ferland received a Ph.D degree in Operations Research from Stanford University, Stanford, Ca. in 1971. Currently, he is a full Professor in the Department of Computer Science and Operations Research at the University of Montreal, Montreal, QC, Canada.

His research interests include fundamental projects related to generalised convexity and generalised fractional programming. He is also working on applied research projects using large scale mathematical programming methods, and metaheuristic methods to deal with combinatorial programming problems and applications in different contexts: mining, forestry, transportation, healthcare, scheduling,...