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An Improved Fair Allocation Based on Contribution Rate and Its Application

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  • Hai-jun Xiao
  • Zhen-min Mo
  • Jin-hua Cheng

Abstract

Oil production task allocation (OPTA) is affected by various factors, and each one has a different impact on oil production. Therefore, the fair distribution of production task to each production branch is really a hard work for an oil company, so a fair allocation based on contribution rate (ABCR) has been proposed to solve this problem in this paper. The algorithm of ABCR, unlike other existing algorithms, takes into account the differences of members’ contribution (DMC), which can be expressed by member contribution rate (MCR) based on the certainty and uncertainty factors. Two steps are implemented to gain the differences of members’ contribution. First, we use Principal Component Analysis (PCA) to reduce factors for certain factor and construct a new factor with Analytic Hierarchy Process (AHP) for uncertain factor. Then, the MCR is evaluated by AHP. Based on member contribution rate, member goal, and alliance target, a fair allocation can be obtained by ABCR. Finally, we propose an evaluation criterion for allocation. Case study shows that the resource allocation results of ABCR not only are more reasonable than those of the other methods but also can prevent unfair allocation and enhance the production environment, thereby improving the enthusiasm for production.

Suggested Citation

  • Hai-jun Xiao & Zhen-min Mo & Jin-hua Cheng, 2018. "An Improved Fair Allocation Based on Contribution Rate and Its Application," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-9, July.
  • Handle: RePEc:hin:jnlmpe:2426810
    DOI: 10.1155/2018/2426810
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