Lluís Puigjaner Corbella

Scenario-based price negotiations vs. game theory in the optimization of coordinated supply chains

A scenario-based negotiation (SBN) win-to-win approach is proposed for the optimization of coordinated decentralized multi-site multi-product Supply Chains (SCs) in a competitive environment. Based on non-symmetric roles, the leader aims to settle its offer taking into account the uncertain reaction of the follower, which behavior is represented by a probability of acceptance. Different negotiation scenarios, based on considering Standalone, Cooperative, and Non-Cooperative SCs are analyzed for the negotiation, resulting in different MINLP tactical models, which are illustrated using a case study with different “follower” SCs around an industrial production SC “leader”. On the other hand, a Stackelberg non-cooperative bi-level MINLP game model is built and solved for the same case study. The Non-Cooperative Negotiation Scenario (NCNS) proves to be more adequate, leading to higher individual profits expectations.

Managing financial risk in the coordination of supply chain and product development decisions

In todays highly competitive marketplace, supply chain (SC) and product development activities should be coordinated and synchronized so that market demand, product release and capacity requirements are matched in a financially sustainable fashion. In this work, an integrated model is developed which incorporates simultaneous treatment of SC design-planning and R&D decisions in the pharmaceutical industry. Moreover, the aforementioned cross-functional model embeds a capital budgeting formulation enabling the quantitative assessment of the firms’ value. The model also considers the endogenous uncertainty associated with product test outcomes during the development process. To tackle this problem, a scenario based multi-stage stochastic mixed integer linear programming (MILP) formulation is proposed. This model includes risk constraints which allow finding optimal solutions within accepted risk levels. A decomposition technique is applied in order to reduce the computational effort required for the solution of the monolithic model, thus facilitating the solution of realistic industrial problems of moderate scale.Chemical batch process management, regardless of the level where its analysis is focused (such as pre-formulation and new process development, supply chain management, scheduling, process control, fault analysis, etc.) implies the collection and exploitation of huge amounts of data, which should be viewed as sources of information. Consequently, the information infrastructure which supports different activities by streamlining information gathering, data integration, model development and decision making is a crucial component towards process improvement/optimization. In this work it a Batch Process Ontology (BaPrOn) is presented, wherein different concepts regarding batch processes are categorized, and the relationships between them are examined and structured. Properties and relationships are introduced in agreement with ISA-88 standard, which provides a solid and transparent framework for integrating batch-related information.