A mathematical negotiation mechanism for distributed procurement problems and a hybrid algorithm for its solution.

تقدم المقالة آلية تفاوض رياضية تهدف إلى حل تحديات الشراء الموزع ضمن سلسلة إمداد السيارات، باستخدام خوارزمية هجينة كحل. تتميز هذه الآلية بنهج برمجة ثنائية المستوى حيث يقود المشتري ويتبع الموردون، مع التركيز على تقليل تكاليف الشراء والنقص. تُظهر الخوارزمية الهجينة المقدمة، التي تجمع بين تحسين سرب الجسيمات (PSO) وبحث هيوريستيكي A، كفاءة وجودة حل تفوق الطرق الأخرى. بالإضافة إلى ذلك، تؤكد الدراسة على الآثار العملية للنموذج في تحسين شراكات الموردين وتحسين استراتيجيات الشراء، بينما تتناول أيضًا حساب تكاليف المخزون والتسليم في إدارة سلسلة الإمداد. [Extracted from the article]

In this paper, a mathematical negotiation mechanism is designed to minimize the negotiators' costs in a distributed procurement problem at two echelons of an automotive supply chain. The buyer's costs are procurement cost and shortage penalty in a one-period contract. On the other hand, the suppliers intend to solve a multi-period, multi-product production planning to minimize their costs. Such a mechanism provides an alignment among suppliers' production planning and order allocation, also supports the partnership with the valued suppliers by taking suppliers' capacities into account. Such a circumstance has been modeled via bi-level programming, in which the buyer acts as a leader, and the suppliers individually appear as followers in the lower level. To solve this nonlinear bi-level programming model, a hybrid algorithm by combining the Particle Swarm Optimization (PSO) algorithm with a heuristic algorithm based on A search is proposed. The heuristic A algorithm is embedded to solve the Mixed-Integer Nonlinear Programming (MINLP) sub-problems for each supplier according to the received variable values determined by PSO system particles (buyer's Request For Quotations (RFQs)). The computational analyses have shown that the proposed hybrid algorithm called PSO-A outperforms PSO-Simulated Annealing (PSO-SA) and PSO-Greedy algorithms. © 2024 Sharif University of Technology. All rights reserved. [ABSTRACT FROM AUTHOR]

Copyright of Scientia Iranica. Transaction E, Industrial Engineering is the property of Scientia Iranica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)