Optimising a mathematical model for a multi-sized public bicycle sharing system considering built-in control centres under fuzzy demand, a case study

Ahangar, Shahin Sadeghi; Heidari, Mojtaba; Aghsami, Amir; Jolai, Fariborz

doi:10.1080/23302674.2021.2004259

Cited by 3 publications

(1 citation statement)

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“…GOA is a type of evolutionary algorithm that is somehow developed from the genetic algorithm and inspired by the environment so that it imitates the demeanor of sudden movement of grasshoppers toward food sources in nature (Salari et al , 2022). Like other nature-inspired algorithms, GOA categorizes the search process into exploration and exploitation stages (Ahangar et al , 2021). Under exploration, grasshoppers are abruptly moved from one point to another, whereas they locally move in the course of exploitation.…”

Section: Solution Methodsmentioning

confidence: 99%

A scenario-based collaborative problem for a relief supply chain during post-disaster under uncertain parameters: a real case study in Dorud

Bakhshi

Aghsami

Rabbani

2022

JM2

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Purpose Unfortunately, the occurrence of natural disasters is inevitable all over the world. Hence, this paper aims to analyze a scenario-based collaborative problem in a relief supply chain (RSC), where nongovernmental organizations can participate in relief activities with governmental organizations. This study focuses on location-allocation, inventory management and distribution planning under uncertain demand, budget, transportation and holding costs where government and private distribution centers receive relief items from suppliers then send them to affected areas. The performance of the proposed model is surveyed in a real case study in Dorud. Design/methodology/approach This paper develops a nonlinear mixed-integer programming model that seeks to maximize the coverage of demand points and minimize operating costs and traveled distance. The linear programming-metric technique and grasshopper optimization algorithm are applied to survey the model's applicability and efficiency. Findings This study compares noncollaborative and collaborative cases in terms of the number of applied distribution centers and RSC's goals, then demonstrates that the collaborative model not only improves the coverage of demand points but also minimizes cost and traveled distance. In fact, the presented approach helps governments efficiently surmount problems created after a disaster, notwithstanding existing uncertainties, by determining a strategic plan for collaboration with nongovernmental organizations for relief activities. Originality/value Relief strategies considered in previous research have not been sufficiently examined from the perspective of collaboration of governmental and nongovernmental organizations and provided an approach to develop the coverage of affected areas and reducing costs and traveled distance despite various uncertainties. Hence, the authors aim to manage RSCs better by offering a mathematical model whose performance has been proved in a real case study.

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Section: Solution Methodsmentioning

confidence: 99%