and decentralized planning systems. Centralized systems can theoretically optimize supply chain performance although its implementation requires a high degree of information exchange among supply chain partners. This leads to difficulties when independent partners do not want to share information. In order to address these difficulties, decentralized systems are designed for supply chains where each member is a separate economic entity that makes its operational decisions independently, yet with some minimal level of information sharing.In this thesis, we first review supply chain operations planning coordination methods from centralized to decentralized approaches proposed in the literature. Next, we propose a classification scheme of these approaches based on the technology used by the authors. Finally, we identify research opportunities.Second, we propose a decentralized operations planning coordination mechanism referred to as mutual adjustment search (MAS), which is based on a negotiation-like mutual adjustment of planning decisions with financial incentives and rooted in mathematical programming. This mechanism, unlike traditional centralized system, involves two independent enterprises linked by material and non-strategic information flows, which interact with each other in order to coordinate their operations planning, and to improve their individual and collective performance.In this approach, only a few coordination solutions (pairs of coordinated operations plans) are considered and computational analysis shows that this coordination mechanism has the potential to improve global profit, while maintaining fairness in terms of revenue sharing.Finally, in order to develop an approach capable of supporting the dynamic coordination of operations planning in a rolling horizon context, this thesis first proposes a negotiation strategy for the supplier, as well as a revenue sharing protocol. Computational analysis shows that the proposed approach produces a win-win strategy for two partners of supply chain and improves the results of upstream planning. viii Keywords: Supply chain management, coordination, incentive mechanism, operations planning, mathematical programming, mutual adjustment search, and operation research. ix