An Imperialist Competitive Algorithm for a Real-World Flexible Job Shop Scheduling Problem

Traditional planning and scheduling techniques still hold important roles in modern smart scheduling systems. Realistic features present in modern manufacturing systems need to be incorporated into these techniques. The real-world problem addressed here is an extension of flexible job shop scheduling problem and is issued from the modern printing and boarding industry. The precedence between operations of each job is given by an arbitrary directed acyclic graph rather than a linear order. In this paper, we extend the traditional FJSP solutions representation to address the parallel operations. We propose an imperialist competitive algorithm for the problem. Several instances are used for the experiments and the results show that, for the considered instances, the proposed algorithm is faster and found better or equal solutions compared to the state-of-the-art algorithms

An Effective Hybrid Imperialist Competitive Algorithm and Tabu Search for an Extended Flexible Job Shop Scheduling Problem

An extended version of the flexible job shop problem is tackled in this work. The investigated extension of the classical flexible job shop problem allows the precedences between the operations to be given by an arbitrary directed acyclic graph instead of a linear order. The problem consists of designating the operations to the machines and sequencing them in compliance with the supplied precedences. The goal in the present work is the minimization of the makespan. In order to produce reasonable outcomes in acceptable time, a hybrid imperialist competitive algorithm and tabu search is proposed to solve the problem. Numerical experiments assess the efficiency of the proposed method and compare it with well-known scheduling algorithms

A hybrid method for the lot sizing problem

Neste trabalho, abordamos métodos de resolução para o problema de dimensionamento de lotes que contempla o planejamento da produção de vários produtos em múltiplas máquinas. A fabricação dos produtos consome tempo de produção e preparação de uma capacidade de produção limitada. A demanda pelos produtos é conhecida e pode ser atendida com atraso durante um horizonte de planejamento finito. O objetivo é minimizar a soma dos custos de produção, preparação para a produção, estoque dos produtos e atraso na entrega destes. Em uma primeira etapa, desenvolvemos uma busca tabu determinística baseada em outra, aleatória, que foi apresentada na literatura. Com isso, realizamos uma análise sobre a influência de fatores aleatórios sobre heurísticas do tipo busca tabu quando aplicadas ao problema estudado. Posteriormente, desenvolvemos um método híbrido baseado em busca tabu, branch-and-cut e programação linear para a resolução do problema. Nos testes computacionais realizados, o método proposto mostrou-se competitivo quando comparado a outras heurísticas apresentadas na literaturaThis paper proposes two methods to solve the capacitated lot-sizing problem with multiple products and parallel machines. The manufacturing of products consumes machines capacity (production time and setup time), which is scarce. The demand for the products is known and can be met with backlogging. The objective is to minimize the sum of production, setup, holding and backlog costs. In a first step, we developed a deterministic tabu search heuristic based on a random version from the literature and then conducted an analysis of the influence of random factors on tabu search heuristics when applied to solve the studied problem. Subsequently, we designed a hybrid method based on tabu search, branch-andcut and linear programming. Computational experiments show that this hybrid method is competitive with other heuristics presented in the literatur

O problema de corte de peças irregulares

The two-dimensional irregular cutting and packing problems (aka nesting problems) have been studied over the past six decades and consist in cutting (packing) convex and non-convex small pieces from (in) large boards without overlapping. There are several variants of this problem that are defined according to the board shapes and the objective of each problem. There are a number of heuristics proposed in the literature to solve irregular cutting and packing problems, but only few mixed-integer programming models. Specifically, these models were developed for the irregular strip packing problem, that consists in packing pieces into a single board with fixed width and length to be minimized. For the other problem variants, there is no exact methods presented in the literature. The main difficulty in solving irregular cutting and packing problems is how to handle with the geometric constraints. These constraints depend on the type of placement of the pieces on the board that can be continuous or discrete. In this thesis, we present two mixed-integer programming models for the irregular strip packing problem in which the pieces can be continuously placed on the board. These models do not demand complex structures to be built. We also present a new dot data structure to store the information on the placement of the pieces and overlapping positions bringing flexibility and efficiency to discrete approaches. Using this structure, a matheuristic is proposed, combining the advantages of the models with discrete and continuous placement positions for the pieces on the board. Furthermore, constraint programming models for several variants of irregular cutting and packing problems are exploited. For some variants, these models are the first modelling representation. A new global constraint is developed to eliminate the overlap among pieces. Computational experiments were conducted to evaluate the developed approaches.Os problemas de corte e empacotamento de peças irregulares bidimensionais vêm sendo estudados há décadas e consistem em cortar (empacotar) peças menores, convexas e não convexas, a partir de (em) placas maiores de forma a não se sobreporem. Existem diversas variantes deste problema, definidas de acordo com o formato da placa e objetivo de cada problema. Na literatura, muitas heurísticas foram propostas para a resolução dos problemas de corte e empacotamento de peças irregulares, porém, poucos modelos de programação inteira mista podem ser encontrados. Especificamente, estes modelos foram desenvolvidos para o problema de empacotamento em faixa, que consiste em empacotar as peças em uma placa de largura fixa e comprimento a ser minimizado. Para as demais variantes do problema, não existem métodos exatos propostos na literatura. A principal dificuldade na resolução dos problemas de corte e empacotamento de peças irregulares está na manipulação das restrições geométricas. Estas restrições dependem do tipo de posicionamento das peças na placa, que pode ser discreto ou contínuo. Nesta tese, apresentamos dois modelos de programação inteira mista para o problema de empacotamento de peças em faixa, no qual cada peça pode ser alocada de forma contínua na placa. Estes modelos não demandam estruturas complexas para serem construídos. Também apresentamos uma nova estrutura de dados para armazenar informações sobre o posicionamento das peças e as posições de sobreposição, trazendo flexibilidade e eficiência para abordagens discretas. Utilizando esta estrutura, uma matheuristica foi proposta, combinando as vantagens dos modelos com alocação discreta e contínua das peças na placa. Além disso, modelos de programação por restrições para diversas variantes dos problemas de corte e empacotamento de peças irregulares foram explorados. Para algumas variantes, estes modelos são a primeira representação via modelagem. Uma nova restrição global foi desenvolvida para eliminar a sobreposição entre as peças. Experimentos computacionais foram realizados para avaliar as abordagens propostas

MIP models for the irregular strip packing problem: new symmetry breaking constraints

The irregular strip packing problem consists in minimizing the length used to cut a set of pieces from a board with fixed width. Recently, a mixed integer programming model was proposed for the problem, but it may allow a large number of symmetric solutions. In this paper, new symmetry breaking constraints are proposed to improve the model. Computational experiments were performed for instances with convex pieces. The results show the proposed formulation is better than the previous one for most instances, since it improves lower bounds and reduces run-time and number of nodes explored to prove optimality

MIP models for the irregular strip packing problem: new symmetry breaking constraints

The irregular strip packing problem consists in minimizing the length used to cut a set of pieces from a board with fixed width. Recently, a mixed integer programming model was proposed for the problem, but it may allow a large number of symmetric solutions. In this paper, new symmetry breaking constraints are proposed to improve the model. Computational experiments were performed for instances with convex pieces. The results show the proposed formulation is better than the previous one for most instances, since it improves lower bounds and reduces run-time and number of nodes explored to prove optimality