Application of AHP to Multi-Item Inventory Management Using Part Period Algorithm

Hossein Jamshidi,Emeka Dunu,Guy Posey

doi:10.5296/jmr.v13i3.18347

Abstract

This empirical study deals with integration of Analytical Hierarchy Process (AHP) with multi-item inventory management using Part-Period Algorithm. Among many variables which affects inventory systems, this study considers the variables of lot-sizing rules, sequencing, demand pattern, coefficient of variations, and change over cost. AHP is used to pick a sequencing rule and performance criteria. This study describes the application of AHP methodology in the form of multiple tables that will assist production managers in a Group Technology environment, to minimize employee and machine idleness. It will help managers make decisions on production order quantity, the sequence in which jobs should enter work centers, and in the determination of uniform production cycle times.

Highlights

According to Decision Support System Resources (Powers, 2021), Analytical Hierarchy Process (AHP) is defined as “an approach to decision making that involves structuring multiple choice criteria into a hierarchy, assessing the relative importance of these criteria, comparing alternatives for each criterion, and determining an overall ranking of the alternatives”, AHP provides a recognized effective approach to deal with complex decision making by organizing and assessing alternatives against a hierarchy of multifaceted objectives
Order quantities can be calculated for the Part Period Algorithm (PPA) Algorithm, high cost ratio, high coefficient of variation, with six demand patterns
In PPA, the decision as to when and how much to produce is based on comparison of EPP (Economic Part Period) to cumulative part period (CPP) (Cumulative Part Period)

Summary

Introduction

According to Decision Support System Resources (Powers, 2021), Analytical Hierarchy Process (AHP) is defined as “an approach to decision making that involves structuring multiple choice criteria into a hierarchy, assessing the relative importance of these criteria, comparing alternatives for each criterion, and determining an overall ranking of the alternatives”, AHP provides a recognized effective approach to deal with complex decision making by organizing and assessing alternatives against a hierarchy of multifaceted objectives. It tremendously reduces the decision-making cycle, and helps capture both subjective and objective evaluation measures (Parcom, 2007). After groups are formed in a GT environment, three associated questions to be answered are:

Methods

Results

Conclusion