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Routing decisions for Buddhist pilgrimage: an elitist genetic algorithm approach

Author

Listed:
  • Rabin K. Jana

    (Indian Institute of Management Raipur)

  • Dinesh K. Sharma

    (University of Maryland Eastern Shore)

  • Subrata K. Mitra

    (Institute of Management Technology)

  • Bidushi Chakraborty

    (Institute of Engineering & Management)

Abstract

Pilgrimage is a historic and inseparable event in Buddhism. The event is significant for Indian tourism and its long-term viability. There are several critical Buddhist pilgrimage-related problems. One such problem is determining the best route decisions to cover main Buddhist sites. This problem has never been mathematically studied. In this paper, we formulate the Buddhist pilgrimage problem as an asymmetric traveling salesman problem. We focus on foreign pilgrims who will travel to India by air. We consider two cases - (i) closed tour in which pilgrims’ port of entry and exit are the same, (ii) open tour in which pilgrims’ port of entry and exit are different. These problems are combinatorial in nature. We propose an elitist genetic algorithm to suggest to pilgrims the best route for which the distance traveled is minimum. To illustrate the proposed approach, we consider fifteen major Buddhist sites and two ports of entry and provide the best pilgrimage decisions for open and closed tour options. The results show that the pilgrims should prefer the port of entry Mumbai in both closed and open tour problems. Also, the open tour decision is the best for the pilgrims, in which the journey starts from Mumbai and finishes at New Delhi.

Suggested Citation

  • Rabin K. Jana & Dinesh K. Sharma & Subrata K. Mitra & Bidushi Chakraborty, 2024. "Routing decisions for Buddhist pilgrimage: an elitist genetic algorithm approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(2), pages 609-620, February.
    • Handle: RePEc:spr:ijsaem:v:15:y:2024:i:2:d:10.1007_s13198-021-01400-8
    DOI: 10.1007/s13198-021-01400-8
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    References listed on IDEAS

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    1. Sharma, Dinesh K. & Jana, R.K., 2009. "A hybrid genetic algorithm model for transshipment management decisions," International Journal of Production Economics, Elsevier, vol. 122(2), pages 703-713, December.
    2. Kusum Deep & Hadush Mebrahtu & Atulya K. Nagar, 2018. "Novel GA for metropolitan stations of Indian railways when modelled as a TSP," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(3), pages 639-645, June.
    3. Adane Abebaw Gessesse & Rajashree Mishra & Mitali Madhumita Acharya & Kedar Nath Das, 2020. "Genetic algorithm based fuzzy programming approach for multi-objective linear fractional stochastic transportation problem involving four-parameter Burr distribution," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(1), pages 93-109, February.
    4. Mukesh Kumar & Sanjeev Prashar & RK Jana, 2019. "Does international tourism spur international trade and output? Evidence from wavelet analysis," Tourism Economics, , vol. 25(1), pages 22-33, February.
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