An integrated manufacturing/remanufacturing system is considered in this paper with the aim of scheduling the operations of the manufacturing plant. The system is partially closed in the sense that the raw materials, necessary for assembling the final products, can be obtained both from an internal remanufacturing plant (which disassembles returned products) and from external suppliers. The manufacturing system is modelled as a flexible flow shop whose stages represent the different assembly phases leading to the final products. In this paper, an original event-based mixed integer programming (MIP) formulation is presented, whose objective consists of minimizing, as primary objective, the weighted number of tardy jobs and, as secondary ones, the fixed and variable purchase costs of raw materials possibly acquired from external suppliers. Due to the complexity of the problem, the MIP formulation can be used to solve only small instances. For this reason, a matheuristics is proposed, which consists of three interoperating mathematical programming models: the first model assigns the jobs to the machines; the second model sequences the jobs on the machines; the third model defines the external supplies, taking into account the component availability constraints. A preliminary computational analysis shows the effectiveness of the proposed algorithm.

### A Matheuristics for the Single-period Lot Scheduling with Component Availability Constraints in a Partially Closed Manufacturing/Remanufacturing System

#### Abstract

An integrated manufacturing/remanufacturing system is considered in this paper with the aim of scheduling the operations of the manufacturing plant. The system is partially closed in the sense that the raw materials, necessary for assembling the final products, can be obtained both from an internal remanufacturing plant (which disassembles returned products) and from external suppliers. The manufacturing system is modelled as a flexible flow shop whose stages represent the different assembly phases leading to the final products. In this paper, an original event-based mixed integer programming (MIP) formulation is presented, whose objective consists of minimizing, as primary objective, the weighted number of tardy jobs and, as secondary ones, the fixed and variable purchase costs of raw materials possibly acquired from external suppliers. Due to the complexity of the problem, the MIP formulation can be used to solve only small instances. For this reason, a matheuristics is proposed, which consists of three interoperating mathematical programming models: the first model assigns the jobs to the machines; the second model sequences the jobs on the machines; the third model defines the external supplies, taking into account the component availability constraints. A preliminary computational analysis shows the effectiveness of the proposed algorithm.
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2016
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Utilizza questo identificativo per citare o creare un link a questo documento: `https://hdl.handle.net/11567/845944`
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