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A new framework for warehouse assessment using a Genetic-Algorithm driven analytic network process.

Wafa' H AlAlaween1, Abdallah H AlAlawin2, Mahdi Mahfouf3

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This study introduces a novel warehouse assessment scheme by integrating the genetic algorithm (GA) and analytic network process (ANP). The method identifies competitive advantages and areas for improvement in warehouse operations.

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Area of Science:

  • Operations Research
  • Supply Chain Management
  • Industrial Engineering

Background:

  • Warehouse performance assessment is crucial for identifying competitive advantages and areas for improvement.
  • Existing methods may lack the ability to fully capture complex interrelationships between assessment criteria.
  • A need exists for a robust and adaptable warehouse assessment framework.

Purpose of the Study:

  • To develop a novel warehouse assessment scheme by integrating the genetic algorithm (GA) and the analytic network process (ANP).
  • To determine the relative importance and interrelationships of warehouse performance criteria.
  • To create an assessment tool that avoids traditional pairwise comparisons.

Main Methods:

  • Integration of the genetic algorithm (GA) with the analytic network process (ANP) to create a hybrid algorithm.
  • Defining key criteria influencing warehouse performance.
  • Assigning importance and strength values to criteria and their interrelationships using the GA-ANP algorithm.
  • Developing an audit checklist based on the defined criteria.

Main Results:

  • The proposed GA-ANP algorithm successfully determined the relative importance and interrelationships of warehouse performance criteria.
  • The integrated scheme linguistically presents importance and strength, circumventing pairwise comparisons.
  • Validation on 45 warehouses demonstrated the scheme's ability to identify competitive advantages and areas for improvement.

Conclusions:

  • The novel GA-ANP integrated warehouse assessment scheme is effective in evaluating warehouse performance.
  • The method provides a comprehensive approach to understanding warehouse competitive advantages and identifying areas needing enhancement.
  • This approach offers a valuable tool for optimizing warehouse operations and strategy.