Bi-criteria transportation problem with multiple parameters

Singh, Sonia; Singh, Shalabh

doi:10.1007/s10479-018-2825-z

Cited by 5 publications

(1 citation statement)

References 21 publications

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“…An approach to address such an imbalanced constellation with multiple parameters is the bi-criteria transportation problem. A study conducted by Singh and Singh (2018) investigated a multi-objective problem consisting of shipment cost and time required, of which the latter constituted a bottleneck. Applying multiple-choice programming, the researchers found that incorporating multiple-choice parameters resulted in a more flexible transportation model.…”

Section: Travel Costmentioning

confidence: 99%

A Linear Programming Model for Optimal Check Airmen Allocation to Minimize Travel Costs

Garcia¹,

Jädicke²,

Truong³

2020

CARI

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Across the globe, civil aviation authorities (CAA) require pilots to be examined upon completion of their flight training and at regular intervals to uphold their pilot's license. These flight examinations, or checkrides, are conducted by designated flight examiners and CAA pilots. While government employees are dispatched to different locations to conduct such exams, designated check airmen may only conduct checkrides that have limited coverage in the geographic area in which those exams are allowed. Thus, if the demand for checkrides at a given location is higher than the number of available designated flight examiners, those employed by the CAA may have to travel to satisfy the need for checkrides, incurring additional costs to these organizations. This paper aims at developing an optimization model using linear programming to find the optimal number of checkrides at different locations that minimizes the total travel cost of government check airmen (GCA) conducting checkrides, considering specific travel costs between locations. Based on a realistic set of initialization parameters, the optimal solution showed a minimal travel cost of $35,827.30 for six months. This model could be applied to other areas that may face a similar decision-making process.

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Section: Travel Costmentioning

confidence: 99%