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AUTOMATION OF OPTIMAL PRODUCTION SCHEDULES FOR A CERTAIN CLASS
OF DETERMINISTIC INVENTORY PROBLEMS USING DYNAMIC PROGRAMMING
1
Ukwu, Chukwunenye&
2
Tanko, Ishaya
1
Department of Mathematics, University of Jos, P.M.B 2084, Jos, Plateau State, Nigeria.
2
Department of Computer Science, University of Jos, P.M.B 2084, Jos, Plateau State, Nigeria .
ABSTRACT
This research article conceptualized, formulated and designed Excel solution templates and
corresponding exposition for optimal production schedules for a certain class of deterministic
inventory problems. The article also provided illustrative examples which demonstrated the
efficiency, utility and processing power of the solution templates. The deployment of the solution
templates circumvents the inherent tedious, and prohibitive manual computations associated with
dynamic programming formulations and recursions and may be optimally appropriated for sensitivity
analyses on each model.
Keywords: Automation, Deterministic, Dynamic programming recursions, Excel, Inventory, Optimal
production schedules, Solution Templates.
1. INTRODUCTION
The need for automation of processesis imperative; this is especially so of optimal policy
prescriptionsof dynamic programming-based outputs with resulting tremendous savings in time, cost
and energy. Consequently, any desired levels of sensitivity analyses can be easily undertaken and
accomplished with great rapidity; needless to say that long horizon lengths can be assigned
henceforth in such problems that hitherto could hardly be contemplated due to the „curse of
dimensionality‟ of dynamic programming recursions.
Ukwu [1,2] designed and implemented Excel solution templates for optimal investment strategies and
the corresponding optimal rewards, for the largest class of certain probabilistic dynamic investment
International Research Journal of Mathematics, Engineering and IT
ISSN: (2348-9766)
Association of Academic Researchers and Faculties (AARF)
Impact Factor- 5.489 Volume 7, Issue 2, February 2020
Website- www.aarf.asia , Email : editor@aarf.asia , editoraarf@gmail.com