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Optimization of Fresh Food Distribution Route Using Genetic Algorithm with the Best Selection Technique

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Constraint Handling in Metaheuristics and Applications

Abstract

All along the food supply chain, managers face the challenge of making important cost-optimized decisions relating to transportation and storage conditions. An efficient management of food products requires the consideration of their perishable nature to solve the safety problem, and logistics efforts in minimizing the total cost while maintaining the quality of food products above acceptable levels. This paper addresses a methodology to resolve a capacitated model for food supply chain (FSC). The model is a constrained mixed integer nonlinear programming problem (MINLP) that computes the cost of quality internally for a three echelon FSC, to minimize the total cost under overall quality level constraints, due to the perishable nature of the products, and the other constraints of demand, capacity, flow balance, and cost. The practical application of the model is demonstrated using two approaches: an exact method based on the Branch & Bound technique, and a Genetic Algorithm solution method. Then, we propose a comparison of different GA selection strategies, such as Tournament, Stochastic Sampling without Replacement, and Boltzmann tournament selection; the performance of each selection method is studied using paired “T-Test” of statistical analysis. The results of computational testing are reported and discussed, and implications and insights for managers are provided by studying instances of practical and realistic size. It was evident that the tournament selection is more likely to produce a better performance than the other selection strategies.

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Abbreviations

B&B:

Branch and Bound

COQ:

Cost of Quality

CPU:

Central Processing Unit

FSC:

Food Supply Cain

GA:

Genetic Algorithm

MILP:

Mixed Integer Linear Programming

MINLP:

Mixed Integer Non-Linear Programming

PAF:

Prevention-Appraisal-Failure

PSO:

Particle Swarm Optimization

QL:

Quality Level

RBF:

Radial Basis Function

SA:

Simulated Annealing

SC:

Supply Chain

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Author information

Authors and Affiliations

  1. Mechanical Engineering Laboratory, Faculty of Science and Techniques, Sidi Mohammed Ben Abdellah University, B.P. 2202, Route d’Imouzzer, FEZ, Morocco

    Douiri Lamiae, Abdelouahhab Jabri & Abdellah El Barkany

  2. ECAM-EPMI, 13 Boulevard de l’Hautil, 95092, Cergy-Pontoise cedex, France

    A.-Moumen Darcherif

Authors
  1. Douiri Lamiae
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  2. Abdelouahhab Jabri
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  3. Abdellah El Barkany
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  4. A.-Moumen Darcherif
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Corresponding author

Correspondence to Douiri Lamiae .

Editor information

Editors and Affiliations

  1. Symbiosis Centre for Research and Innovation, Symbiosis International University, Pune, Maharashtra, India

    Anand J. Kulkarni

  2. Artificial Intelligence Research Center, University of Veracruz, Xalapa, Veracruz, Mexico

    Efrén Mezura-Montes

  3. School of Automation, Central South University, Changsha, China

    Yong Wang

  4. Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW, Australia

    Amir H. Gandomi

  5. Monash University Malaysia, Selangor, Malaysia

    Ganesh Krishnasamy

Appendix

Appendix

See Tables 16 and 17.

Table 16 Parameters for the COFQ function
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Table 17 Food supply chain network parameters
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Lamiae, D., Jabri, A., El Barkany, A., Darcherif, AM. (2021). Optimization of Fresh Food Distribution Route Using Genetic Algorithm with the Best Selection Technique. In: Kulkarni, A.J., Mezura-Montes, E., Wang, Y., Gandomi, A.H., Krishnasamy, G. (eds) Constraint Handling in Metaheuristics and Applications. Springer, Singapore. https://doi.org/10.1007/978-981-33-6710-4_8

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  • DOI: https://doi.org/10.1007/978-981-33-6710-4_8

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