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Constraint Optimization Model for Dynamic Parking Space Allocation.

Abdelrahman Osman Elfaki1, Wassim Messoudi1, Anas Bushnag1

  • 1Faculty of Computers & Information Technology, University of Tabuk, Tabuk 47512, Saudi Arabia.

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Summary
This summary is machine-generated.

This study introduces a constraint optimization model for dynamic car parking systems. It intelligently assigns parking slots considering user schedules and constraints, improving efficiency.

Keywords:
constraint optimization modeldynamic parking space allocationparking management system

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Area of Science:

  • Operations Research
  • Intelligent Transportation Systems
  • Computer Science

Background:

  • Managing car parking systems involves complex organizational and operational constraints.
  • Dynamic allocation of parking spaces presents significant challenges.
  • Existing systems often lack intelligent prioritization and dynamic distribution capabilities.

Purpose of the Study:

  • To introduce a constraint optimization model for dynamic parking space allocation.
  • To develop and present an ad hoc algorithm for efficient parking management.
  • To provide an intelligent prioritization mechanism considering user schedules and parking constraints.

Main Methods:

  • Development of a constraint optimization model for dynamic parking allocation.
  • Proposal and explanation of a novel ad hoc algorithm.
  • Implementation of the proposed model to demonstrate applicability.
  • Construction of a benchmark with well-defined metrics for validation.

Main Results:

  • The proposed model demonstrates effective dynamic parking space allocation.
  • The intelligent prioritization mechanism successfully considers user schedule shifts and parking constraints.
  • The ad hoc algorithm facilitates dynamic distribution of suitable parking slots.
  • Validation through a constructed benchmark confirms the model's performance.

Conclusions:

  • The developed constraint optimization model offers an intelligent solution for dynamic car parking management.
  • The proposed approach enhances parking efficiency by dynamically assigning suitable slots based on user needs and system constraints.
  • The research contributes a validated method for intelligent parking prioritization and allocation.