abstract

A two-phase genetic algorithm for incorporating environmental considerations with production, inventory and routing decisions in supply chain networks

Authors:

Nader Azad,

Adel Aazami,

Ali Papi,

Armin JabbarzadehAuthors Info & Claims

GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion

Pages 41 - 42

https://doi.org/10.1145/3319619.3326781

Published: 13 July 2019 Publication History

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Abstract

In this paper, we study an integrated production-inventory-routing planning (PIRP) problem which addresses important decisions in the supply chains and it is classified as an NP-hard problem. Studies shows that companies solving their production, inventory and routing decisions simultaneously, can reduce their total costs significantly and respond to the customers' needs efficiently. Nowadays due to strict regulations, companies must take into account environmental considerations as well as cost minimization in their processes. Therefore, in this paper we develop a mixed-integer linear programming model to formulate the green PIRP (GPIRP) problem which optimizes the economic and social dimensions of the supply chains. Also, we propose a two-phase genetic algorithm (GA) in which the inventory and production decisions are solved in the first phase and the vehicle routing and transportation decisions are solved in the second phase. In the computational experiments we conduct sensitivity analysis to investigate the efficiency of our proposed solution algorithm for the large-sized instances

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Khan SQadir ZMunawar HNayak SBudati AVerma KPrakash D(2021)UAVs path planning architecture for effective medical emergency response in future networksPhysical Communication10.1016/j.phycom.2021.10133747(101337)Online publication date: Aug-2021
https://doi.org/10.1016/j.phycom.2021.101337
Dzalbs IKalganova T(2020)Accelerating supply chains with Ant Colony Optimization across a range of hardware solutionsComputers & Industrial Engineering10.1016/j.cie.2020.106610(106610)Online publication date: Jun-2020
https://doi.org/10.1016/j.cie.2020.106610

A two-phase genetic algorithm for incorporating environmental considerations with production, inventory and routing decisions in supply chain networks
1. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies

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Information

Published In

GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion

July 2019

2161 pages

ISBN:9781450367486

DOI:10.1145/3319619

Editor:
Manuel López-Ibáñez
University of Manchester, UK
,
General Chairs:
Anne Auger
Inria and Ecole Polytechnique, France
,
Thomas Stützle
IRIDIA, Université libre de Bruxelles Belgium

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 July 2019

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GECCO '19

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SIGEVO

GECCO '19: Genetic and Evolutionary Computation Conference

July 13 - 17, 2019

Prague, Czech Republic

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

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Khan SQadir ZMunawar HNayak SBudati AVerma KPrakash D(2021)UAVs path planning architecture for effective medical emergency response in future networksPhysical Communication10.1016/j.phycom.2021.10133747(101337)Online publication date: Aug-2021
https://doi.org/10.1016/j.phycom.2021.101337
Dzalbs IKalganova T(2020)Accelerating supply chains with Ant Colony Optimization across a range of hardware solutionsComputers & Industrial Engineering10.1016/j.cie.2020.106610(106610)Online publication date: Jun-2020
https://doi.org/10.1016/j.cie.2020.106610

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Heuristics for a multiperiod inventory routing problem with production decisions

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