Hybrid methods for lot sizing on parallel machines

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Relax and fix heuristics to solve one-stage one-machine lot-scheduling models for small-scale soft drink plants

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Um modelo de otimização inteira mista e heurísticas relax and fix para a programação da produção de fábricas de refrigerantes de pequeno porte

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A linear optimization approach to the combined production planning model

Two fundamental processes usually arise in the production planning of many industries. The first one consists of deciding how many final products of each type have to be produced in each period of a planning horizon, the well-known lot sizing problem. The other process consists of cutting raw materials in stock in order to produce smaller parts used in the assembly of final products, the well-studied cutting stock problem. In this paper the decision variables of these two problems are dependent of each other in order to obtain a global optimum solution. Setups that are typically present in lot sizing problems are relaxed together with integer frequencies of cutting patterns in the cutting problem. Therefore, a large scale linear optimizations problem arises, which is exactly solved by a column generated technique. It is worth noting that this new combined problem still takes the trade-off between storage costs (for final products and the parts) and trim losses (in the cutting process). We present some sets of computational tests, analyzed over three different scenarios. These results show that, by combining the problems and using an exact method, it is possible to obtain significant gains when compared to the usual industrial practice, which solve them in sequence. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

Meta-heuristic approaches for a soft drink industry problem

The present paper evaluates meta-heuristic approaches to solve a soft drink industry problem. This problem is motivated by a real situation found in soft drink companies, where the lot sizing and scheduling of raw materials in tanks and products in lines must be simultaneously determined. Tabu search, threshold accepting and genetic algorithms are used as procedures to solve the problem at hand. The methods are evaluated with a set of instance already available for this problem. This paper also proposes a new set of complex instances. The computational results comparing these approaches are reported. © 2008 IEEE.

Reformulação para um problema integrado de dimensionamento e sequenciamento de lotes

In this paper, some new constraints and an extended formulation are presented for a Lot Sizing and Scheduling Model proposed in the literature. In the production process considered a key material is prepared and is transformed into different final items. The sequencing decisions are related to the order in which the materials are processed and the lot sizing decisions are related to the final items production. The mathematical formulation considers sequence-dependent setup costs and times. Results of the computational tests executed using the software Cplex 10.0 showed that the performance of the branch-and-cut method can be improved by the proposed a priori reformulation.

Strategies to model scheduling decisions to plan the soft drink production process

In this paper we present a mixed integer model that integrates lot sizing and lot scheduling decisions for the production planning of a soft drink company. The main contribution of the paper is to present a model that differ from others in the literature for the constraints related to the scheduling decisions. The proposed strategy is compared to other strategies presented in the literature.

Genetic algorithm, MIP and improvement heuristic applied to the MLCLP with backlogging

The present paper solves the multi-level capacitated lot sizing problem with backlogging (MLCLSPB) combining a genetic algorithm with the solution of mixed-integer programming models and the improvement heuristic fix and optimize. This approach is evaluated over sets of benchmark instances and compared to methods from literature. Computational results indicate competitive results applying the proposed method when compared with other literature approaches. © 2013 IEEE.

Modelos matemáticos para problemas de dimensionamento de lotes com restrições de capacidade e custos de transporte

In this paper, capacitated lot sizing problems in which the classical lot sizing decisions are made considering the transportation costs of the manufactured products were studied. These costs are related to the necessary number of pallets or trucks to pack and/or transport the products from the factory to the warehouse. Three extensions of a mixed integer linear programming model from the literature are considered, representing general cases that are commonly found in companies. These models are tested and evaluated using an optimization package, and a Lagrangian heuristic was developed for one of the extensions proposed.

Modelos matemáticos para o problema integrado de dimensionamento de lotes e corte de estoque undimensional

Pós-graduação em Matemática - IBILCE

Limitantes inferiores par ao problema de dimensionamento de lotes em máquinas paralelas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Reformulações e relaxação Lagrangiana para o problema de dimensionamento de lotes com várias plantas

Pós-graduação em Matemática - IBILCE

Formulações fortes para o problema integrado de dimensionamento e sequenciamento da produção

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estatégias para incorporação das deçisões de sequenciamento em um problema integrado de produção de bebidas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Modelagem do problema integrado de dimensionamento de lotes e corte de estoque em indústria moveleira

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)