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Orientador(es)
Resumo(s)
Industrial companies are seeking for highly flexible strategic and operational solutions to face the requirements of current dynamic markets. The aim of this work is to provide a decision support assessment for the design and scheduling of a multipurpose plant under demand uncertainty, allowing the assessment of alternative risk profile solutions. A general two-stage mixed-integer linear programming (MILP) model is proposed with the goal to maximise the annualised profit of the plant operation under a set of scenarios while minimising the associated financial risk. Considering the long-term investment perspective, the Conditional Value at Risk (CVaR) measure is used to evaluate the likelihood that a specific loss or gain will exceed a certain value at risk. A bi-objective model is formulated using the augmented ε-constraint method to generate an approximation to the Pareto-optimal curve, illustrating the trade-offs between plant profit (with the corresponding design and scheduling decisions) and the associated financial risk. Addressing a set of propositions regarding a case-study, the conclusions highlight the advantages of the risk measure integration in support of the decision-making process, discussing the managerial insights in the assessment of diverse financial outcomes for the solution optimisation.
Descrição
Palavras-chave
Flexible manufacturing systems Design and scheduling optimisation Risk assessment Stochastic programming Conditional value at risk (CVaR)
Contexto Educativo
Citação
VIEIRA, Miguel; [et al] – Assessment of financial risk in the design and scheduling of multipurpose plants under demand uncertainty. International Journal of Production Research. ISSN 0020-7543. (2020), pp. 1-21
Editora
Taylor & Francis