No abstract

A generic tactical model is developed considering third party price policies for the optimization of coordinated and centralized multi-product Supply Chains (SCs). To allow a more realistic assessment of these policies in each marketing situation, different price approximation models to estimate these policies are proposed, which are based on the demand elasticity theory, and result in different model implementations (LP, NLP, and MINLP). The consequences of using the proposed models on the SCs coordination, regarding not only their practical impact on the tactical decisions, but also the additional mathematical difficulties to be solved, are verified through a case study in which the coordination of a production–distribution SC and its energy generation SC is analyzed. The results show how the selection of the price approximation model affects the tactical decisions. The average price approximation leads to the worst decisions with a significant difference in the real total cost in comparison with the best piecewise approximation.Peer ReviewedPostprint (author's final draft

A novel Scenario-Based Dynamic Negotiation approach is proposed for the coordination of decentralized Supply Chains under uncertainty. The relation between the involved organizations (client, provider and third parties) and their respective conflicting objectives is captured through a non-zero-sum and non-symmetric roles SBDN negotiation. The client (leader) designs coordination agreements considering the uncertain reaction of the provider (follower) resulting from the uncertain nature of the third parties, which is modeled as a probability of acceptance. Different negotiation scenarios are studied: i) Cooperative, and ii) Non-Cooperative and iii) Standalone cases. The use of the resulting models is illustrated through a case study with different vendors around a "leader" (client) in a decentralized scenario. Although the usual cooperation hypothesis will allow higher overall profit expectations, using the proposed approach it is possible to identify non-Cooperative scenarios with high individual profit expectations which are more likely to be accepted by all partners.

In this work, an integrated Game Theory (GT) approach is developed for the coordination of multi-enterprise Supply Chains (SCs) in a competitive uncertain environment. The conflicting goals of the different participants are solved through coordination contracts using a non-cooperative non-zero-sum Stackelberg game under the leadership of the manufacturer. The Stackelberg payoff matrix is built under the nominal conditions, and then evaluated under different probable uncertain scenarios using a Monte-Carlo simulation. The competition between the Stackelberg game players and the third parties is solved through a Nash Equilibrium game. A novel way to analyze the game outcome is proposed based on a win–win Stackelberg set of “Pareto-frontiers”. The benefits of the resulting MINLP tactical models are illustrated by a case study with different vendors around a client SC. The results show that the coordinated decisions lead to higher expected payoffs compared to the standalone case, while also leading to uncertainty reduction.Peer ReviewedPostprint (author's final draft

No abstract