The ever-increasing challenges in the business markets have intensified the need for cooperation among all parts of a supply chain. Allocating orders to suppliers in order to satisfy different and conflicting criteria has caused the emergence of new mulita-criteria approaches to address these problems more effectively. This paper investigated an order distribution problem in a real case of Iranian's oil and gas industry. In order to overcome the high complexity of the problem, a hybrid approach combining the features of genetic algorithm (GA) and analytical hierarchy process (AHP) is implemented. An improved version of the central coordination system (CCS) is suggested to integrate and process the various input information of the problem. The selected criteria are based on experts’ opinion in the focused section of the industry. In order to obtain the weights of the criteria, a linear model of the Best-Worst method, a recently developed MCDM method, is implemented. Several candidate solutions are obtained from the results of the proposed hybrid method as the first stage of the study. Then, as the second phase, an AHP approach is used to rank the available solutions. Finally, a sensitivity analysis is conducted to test the reliability of the approach. The results indicated the high robustness of the proposed method in dealing with possible changes in the future.

商业市场中日益严峻的挑战加剧了供应链各部分之间合作的需求。将订单分配给供应商以满足不同和相互矛盾的标准已经导致出现了新的多准则方法来更有效地解决这些问题。本文研究了在伊朗石油和天然气行业的实际案例中的订单分配问题。为了解决该问题的高度复杂性，实现了一种混合方法，该方法结合了遗传算法（GA）和层次分析法（AHP）的特征。建议使用中央协调系统（CCS）的改进版本来集成和处理问题的各种输入信息。选择的标准基于行业重点领域的专家意见。为了获得标准的权重，实施了最差方法（最近开发的MCDM方法）的线性模型。作为研究的第一阶段，从提议的混合方法的结果中获得了几种候选解决方案。然后，作为第二阶段，使用AHP方法对可用解决方案进行排名。最后，进行敏感性分析以测试该方法的可靠性。结果表明，所提出的方法在应对未来可能的变化方面具有很高的鲁棒性。AHP方法用于对可用解决方案进行排名。最后，进行敏感性分析以测试该方法的可靠性。结果表明，所提出的方法在应对未来可能的变化方面具有很高的鲁棒性。AHP方法用于对可用解决方案进行排名。最后，进行敏感性分析以测试该方法的可靠性。结果表明，所提出的方法在应对未来可能的变化方面具有很高的鲁棒性。