221212

MIXED VARIABLE OPTIMIZATION MODEL FOR MEDICAL WASTE REVERSE LOGISTICS NETWORKS USING HYBRID CELLULAR GENETIC ALGORITHM

Article

Last updated: 05 Jan 2025

Subjects

-

Tags

Mathematics and Computer Science

Abstract

The medical waste reverse logistics networks are an attractive topic as the possible public health dangers and ecological ventures for burning a large quantity of medical waste. Reverse logistics networks structures were created for reducing medical waste produced from hospitals for recovery. In this research, a Mixed Variable Optimization (MVO) model is presented for minimizing costs of medical waste reverse logistics networks. The total costs for reverse logistics contain stable cost of opening the gathering stations and treating stations, shipped cost and processing cost, finally a schedule is proposed of flows of medical waste in the network. A hybrid Cellular Genetic Algorithm (CGA) is used for solving the MVO model to be (CGAMV). Pattern search method (PSM) is added to the CGAMV, to be (CGAMV P) to make more intensification on the best solutions in proposed grid. The grid structure and small neighborhood make fast convergence and exploration during genetic algorithm operators. The performance of the CGAMV P algorithm by the presented model is examined on a numerical experiment and it is found promising.

DOI

10.21608/aunj.2018.221212

Keywords

cellular genetic algorithm, Medical Waste, mixed integer programming, reverse logistics networks

Volume

47

Article Issue

2

Related Issue

31544

Issue Date

2018-12-01

Receive Date

2022-02-22

Publish Date

2018-12-01

Page Start

42

Page End

57

Print ISSN

2812-5029

Online ISSN

2812-5037

Link

https://aunj.journals.ekb.eg/article_221212.html

Detail API

https://aunj.journals.ekb.eg/service?article_code=221212

Order

221,212

Publication Type

Journal

Publication Title

Assiut University Journal of Multidisciplinary Scientific Research

Publication Link

https://aunj.journals.ekb.eg/

MainTitle

MIXED VARIABLE OPTIMIZATION MODEL FOR MEDICAL WASTE REVERSE LOGISTICS NETWORKS USING HYBRID CELLULAR GENETIC ALGORITHM

Details

Type

Article

Created At

23 Jan 2023