A note on time/cost tradeoff curve generation for project scheduling with multi-mode resource availability costs

Abstract: In this note we combine two known algorithms and show how they can be used in order to generate tradeoff curves between time and cost for deterministic project scheduling problems with multiple modes and resource availability costs. The approach can handle linear and non-linear non-decreasing cost functions and it is based on the exact algorithm presented in Demeulemeester (1995) for the resource availability cost problem without multiple modes. As the problem is NP-hard, the method is computationally viable to solve only problems of a moderate size. The performance of the combined algorithm is evaluated solving different problem instances generated by the software Progen, and the solutions are compared to the ones generated by a modeling language with the solver CPLEX

Ship Routing with Pickup and Delivery for a Maritime Oil Transportation System: MIP Modeland Heuristics

This paper examines a ship routing problem with pickup and delivery and time windows for maritime oil transportation, motivated by the production and logistics activities of an oil company operating in the Brazilian coast. The transportation costs from offshore platforms to coastal terminals are an important issue in the search for operational excellence in the oil industry, involving operations that demand agile and effective decision support systems. This paper presents an optimization approach to address this problem, based on a mixed integer programming (MIP) model and a novel and exploratory application of two tailor-made MIP heuristics, based on relax-and-fix and time decomposition procedures. The model minimizes fuel costs of a heterogeneous fleet of oil tankers and costs related to freighting contracts. The model also considers company-specific constraints for offshore oil transportation. Computational experiments based on the mathematical models and the related MIP heuristics are presented for a set of real data provided by the company, which confirm the potential of optimization-based methods to find good solutions for problems of moderate sizes

Combinação de abordagens GLSP e ATSP para o problema de dimensionamento e sequenciamento de lotes de produção de suplementos para nutrição animal

In this paper we study the combination of GLSP (General Lot Sizing and Scheduling Problem) and ATSP (Asymmetric Travelling Salesman Problem) approaches with sub-tour elimination and patching to a lot sizing and sequencing problem in the animal nutrition industry. This problem consists of deciding the lots size for each product as well the production sequence of the lots, while meeting demand without backlogs and minimizing production and inventory costs. The coordination of these decisions is a challenge for production scheduling in this industry as the setup times are sequence dependent. The ATSP approaches are compared with relax-and-fix approaches applied to the GLSP (General Lot-sizing and Scheduling Problem) formulated in previous research, using real data from an animal nutrition plant in Sao Paulo state. Portuguese: Neste artigo estudamos a combinação de abordagens GLSP (General Lot Sizing and Scheduling Problem) e ATSP (Asymmetric Travelling Salesman Problem) para o problema de dimensionamento e sequenciamento de lotes na indústria de nutrição animal. Este problema consiste em determinar o tamanho de cada lote de produção para cada produto, assim como a sequência de produção destes lotes, de forma a satisfazer a demanda sem atrasos e minimizar os custos de produção e estoques. Uma dificuldade para a programação da produção nesta indústria é integrar estas decisões, pois os tempos de preparação da linha de produção são dependentes da sequência produtiva e não obedecem a desigualdade triangular. A abordagem proposta é comparada com abordagens relax-and-fix para o modelo GLSP (General Lot-sizing and Scheduling Problem) estudadas em trabalhos anteriores, utilizando dados reais de um estudo de caso de uma fábrica de nutrição animal localizada no interior de São Paulo

Modelagem do problema de programação de bebidas baseado em um modelo do tipo ATSP

Apresentamos neste trabalho uma estratégia baseada em um modelo do caixeiro viajante assimétrico, modelo ATSP (Asymmetric travelling salesman problem) para a programação da produção de bebidas. A estratégia é comparada a uma modelagem onde o sequenciamento é feitopela divisão do período em períodos menores, Ferreira et al. (2009a). Os experimentos computacionais realizados com instâncias baseadas em dados reais indicam que o modelo proposto é competitivo.In this work we present a strategy based on the asymmetric travelling salesman problem, ATSP model, to define de soft drink programming. The strategy is compared with a model in which the sequencing is defined dividing the period in micro-periods Ferreira et al. (2009a). The computational tests with instances based on real data show that the proposed model is competitive

Unequal individual genetic algorithm with intelligent diversification for the lot-scheduling problem in integrated mills using multiple-paper machines

This paper addresses the lot-sizing and scheduling problem of pulp and paper mills involving multiple paper machines. The underlying multi-stage integrated production process considers the following critical units: continuous digester, intermediate stocks of pulp and liquor, multiple paper machines and a recovery line to treat by-products. This work presents a mixed integer programming (MIP) model to represent the problem, as well as a solution approach based on a customized genetic algorithm (GA) with an embedded residual linear programming model. Some GA tools are explored, including literature and new operators, a novel diversification process and other features. In particular, the diversification process uses a new allele frequency measure to change between diversification and intensification procedures. Computational results show the effectiveness of the method to solve relatively large instances of the single paper machine problem when compared to other single paper machine solution methods found in the literature. For multiple paper machine settings, in most runs the GA solutions are better than those obtained for the MIP model using an optimization software.This paper addresses the lot-sizing and scheduling problem of pulp and paper mills involving multiple paper machines. The underlying multi-stage integrated production process considers the following critical units: continuous digester, intermediate stocks of pulp and liquor, multiple paper machines and a recovery line to treat by-products. This work presents a mixed integer programming (MIP) model to represent the problem, as well as a solution approach based on a customized genetic algorithm (GA) with an embedded residual linear programming model. Some GA tools are explored, including literature and new operators, a novel diversification process and other features. In particular, the diversification process uses a new allele frequency measure to change between diversification and intensification procedures. Computational results show the effectiveness of the method to solve relatively large instances of the single paper machine problem when compared to other single paper machine solution methods found in the literature. For multiple paper machine settings, in most runs the GA solutions are better than those obtained for the MIP model using an optimization software

Alternative Mathematical Models and Solution Approaches for Lot-Sizing and Scheduling Problems in the Brewery Industry: Analyzing Two Different Situations

This research proposes new approaches to deal with the production planning and scheduling problem in brewery facilities. Two real situations found in factories are addressed, which differ by considering (or not) the setup operations in tanks that provide liquid for bottling lines. Depending on the technology involved in the production process, the number of tank swaps is relevant (Case A) or it can be neglected (Case B). For both scenarios, new MIP (Mixed Integer Programming) formulations and heuristic solution methods based on these formulations are proposed. In order to evaluate the approach for Case A, we compare the results of a previous study with the results obtained in this paper. For the solution methods and the result analysis of Case B, we propose adaptations of Case A approaches yielding an alternative MIP formulation to represent it. Therefore, the main contributions of this article are twofold: (i) to propose alternative MIP models and solution methods for the problem in Case A, providing better results than previously reported, and (ii) to propose new MIP models and solution methods for Case B, analyzing and comparing the results and benefits for Case B considering the technology investment required