Industrial & Engineering Chemistry Research · 2006 · 38 citations · 13 references
Mathematical ProgrammingSupply Chain OptimizationEngineeringIndustrial EngineeringDisjunctive ProgrammingDifferent TypesMarket DesignOperations ResearchInventory ManagementInventory ControlLogisticsSupply ChainSystems EngineeringQuantitative ManagementManufacturing PlanningSupply Chain ManagementMarketingInteger ProgrammingSupply ManagementProduction PlanningCurrent PlanningBusinessMixed Integer OptimizationPurchasing
The study introduces a novel modeling framework that expands supply‑chain optimization by treating contract type selection as an explicit decision variable. The solution uses disjunctive programming to represent contract choices in short‑ and long‑term production planning, yielding a mixed‑integer linear programming formulation. Two increasingly complex case studies demonstrate the advantages of the proposed models.
This work presents a novel approach for modeling of different types of contracts that a company may sign with its suppliers and customers. The main objective is to expand the scope of current planning and supply chain optimization models by including the selection of the types of contracts as an additional decision. The solution approach relies on representing the decision of choosing different contracts using disjunctive programming for both short-term and long-term production planning models. The resulting formulation is converted into a mixed-integer linear programming (MILP) problem. The advantages of the proposed models are highlighted in two case studies of increasing complexity.
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