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Erschienen in:
Economic Production Quantity (EPQ) Inventory Model for a Deteriorating Item with a Two-Level Trade Credit Policy and Allowable Shortages Kapitel lesen Erstes Kapitel lesen

2020 | OriginalPaper | Buchkapitel

17. Allocation of Order Amongst Available Suppliers Using Multi-objective Genetic Algorithm

verfasst von : Azharuddin Shaikh, Poonam Mishra, Isha Talati

Erschienen in: Optimization and Inventory Management

Verlag: Springer Singapore

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Abstract

In a supply chain, procurement of items is done on the basis of individual performance, whereas the performance of supply chain can be improved by using scientific techniques. In this chapter, we discuss the manufacturer’s problem of procuring several items from the available suppliers; where, supplies from each supplier are constrained. The manufacturer needs to determine which item is to be procured from which supplier and in what quantity. The allocation of order amongst suppliers is done on the basis of multiple criteria such as unit price, quality, supply capacity, delivery time, and unit transportation cost. To demonstrate the scenario, we formulate the mathematical model, which leads to a multi-objective optimization problem. The optimization is done using multi-objective genetic algorithm, which gives a set of Pareto-optimal solutions, then we utilize 3D-RadVis technique to get the best solution. To validate the model, numerical example is presented.

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Vorheriges Kapitel Supply Chain Network Optimization Through Player Selection Using Multi-objective Genetic Algorithm
Nächstes Kapitel Some Studies on EPQ Model of Substitutable Products Under Imprecise Environment
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Metadaten
Titel
Allocation of Order Amongst Available Suppliers Using Multi-objective Genetic Algorithm
verfasst von
Azharuddin Shaikh
Poonam Mishra
Isha Talati
Copyright-Jahr
2020
Verlag
Springer Singapore
Buch
Optimization and Inventory Management

Print ISBN: 978-981-13-9697-7

Electronic ISBN: 978-981-13-9698-4

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-981-13-9698-4_17

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