| Full text | |
| Author(s): |
Total Authors: 3
|
| Affiliation: | [1] Federal University of Mato Grosso do Sul. INMA. Institute of Mathematics - Brasil
[2] University of Campinas. IMECC. Department of Applied Mathematics - Brasil
[3] University of São Paulo. ICMC. Institute of Mathematics and Computer Sciences - Brasil
Total Affiliations: 3
|
| Document type: | Journal article |
| Source: | Pesquisa Operacional; v. 39, n. 3, p. 471-496, 2019-12-02. |
| Abstract | |
ABSTRACT This research addresses a lot sizing and scheduling problem inspired by a real-world production environment where the customers make advanced orders and the industry need to decide which orders will be accepted with the aim of maximizing the profit respecting the production capacity constraints. Orders are composed of different types of items which must be delivered within a given time interval and, moreover, such orders cannot be split. A mixed integer programming (MIP) model is proposed to represent the problem and a MIP-based heuristic is also proposed to deliver good solutions at an acceptable computational time. The heuristic is composed of three phases (construction, deterministic improvement and stochastic improvement phases) and combines relax-and-fix, fix-and-optimize, and iterative MIP based neighborhood search procedures. Computational tests are presented in order to study the efficiency of the proposed approaches. (AU) | |
| FAPESP's process: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | Francisco Louzada Neto |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |