Lot sizing and furnace scheduling in small foundries

A lot sizing and scheduling problem prevalent in small market-driven foundries is studied. There are two related decision levels: (1) the furnace scheduling of metal alloy production, and (2) moulding machine planning which specifies the type and size of production lots. A mixed integer programming (MIP) formulation of the problem is proposed, but is impractical to solve in reasonable computing time for non-small instances. As a result, a faster relax-and-fix (RF) approach is developed that can also be used on a rolling horizon basis where only immediate-term schedules are implemented. As well as a MIP method to solve the basic RF approach, three variants of a local search method are also developed and tested using instances based on the literature. Finally, foundry-based tests with a real-order book resulted in a very substantial reduction of delivery delays and finished inventory, better use of capacity, and much faster schedule definition compared to the foundry's own practice. © 2006 Elsevier Ltd. All rights reserved

Models and Algorithms for Production Planning and Scheduling in Foundries – Current State and Development Perspectives

Mathematical programming, constraint programming and computational intelligence techniques, presented in the literature in the field of operations research and production management, are generally inadequate for planning real-life production process. These methods are in fact dedicated to solving the standard problems such as shop floor scheduling or lot-sizing, or their simple combinations such as scheduling with batching. Whereas many real-world production planning problems require the simultaneous solution of several problems (in addition to task scheduling and lot-sizing, the problems such as cutting, workforce scheduling, packing and transport issues), including the problems that are difficult to structure. The article presents examples and classification of production planning and scheduling systems in the foundry industry described in the literature, and also outlines the possible development directions of models and algorithms used in such systems

A priori reformulations for joint rolling-horizon scheduling of materials processing and lot-sizing problem

In many production processes, a key material is prepared and then transformed into different final products. The lot sizing decisions concern not only the production of final products, but also that of material preparation in order to take account of their sequence-dependent setup costs and times. The amount of research in recent years indicates the relevance of this problem in various industrial settings. In this paper, facility location reformulation and strengthening constraints are newly applied to a previous lot-sizing model in order to improve solution quality and computing time. Three alternative metaheuristics are used to fix the setup variables, resulting in much improved performance over previous research, especially regarding the use of the metaheuristics for larger instances

Decomposition Heuristic With Partial Assignment Approach for MLCLSP-M Problem

This research proposes a heuristic method, which decomposes the Multi-level Multi-item Capacitated Lot Sizing Problem with Multi-workstation (MLCLSP-M) into two phases which are an assignment with given lot size and a partial lot size with given assignment. Each iteration, the sub problem mathematical models are solved with AMPL/CPLEX 8.0.0 solver. An example is present for demonstration of the heuristic. The result indicate that the proposed heuristic (Partial Assignment – Lot size: PA-LS) give a satisfactory solution within faster solving time on comparison with the original mathematical model solving

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

A Production Planning Model for Make-to-Order Foundry Flow Shop with Capacity Constraint

The mode of production in the modern manufacturing enterprise mainly prefers to MTO (Make-to-Order); how to reasonably arrange the production plan has become a very common and urgent problem for enterprises’ managers to improve inner production reformation in the competitive market environment. In this paper, a mathematical model of production planning is proposed to maximize the profit with capacity constraint. Four kinds of cost factors (material cost, process cost, delay cost, and facility occupy cost) are considered in the proposed model. Different factors not only result in different profit but also result in different satisfaction degrees of customers. Particularly, the delay cost and facility occupy cost cannot reach the minimum at the same time; the two objectives are interactional. This paper presents a mathematical model based on the actual production process of a foundry flow shop. An improved genetic algorithm (IGA) is proposed to solve the biobjective problem of the model. Also, the gene encoding and decoding, the definition of fitness function, and genetic operators have been illustrated. In addition, the proposed algorithm is used to solve the production planning problem of a foundry flow shop in a casting enterprise. And comparisons with other recently published algorithms show the efficiency and effectiveness of the proposed algorithm

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

A review of discrete-time optimization models for tactical production planning

This is an Accepted Manuscript of an article published in International Journal of Production Research on 27 Mar 2014, available online: http://doi.org/10.1080/00207543.2014.899721[EN] This study presents a review of optimization models for tactical production planning. The objective of this research is to identify streams and future research directions in this field based on the different classification criteria proposed. The major findings indicate that: (1) the most popular production-planning area is master production scheduling with a big-bucket time-type period; (2) most of the considered limited resources correspond to productive resources and, to a lesser extent, to inventory capacities; (3) the consideration of backlogs, set-up times, parallel machines, overtime capacities and network-type multisite configuration stand out in terms of extensions; (4) the most widely used modelling approach is linear/integer/mixed integer linear programming solved with exact algorithms, such as branch-and-bound, in commercial MIP solvers; (5) CPLEX, C and its variants and Lindo/Lingo are the most popular development tools among solvers, programming languages and modelling languages, respectively; (6) most works perform numerical experiments with random created instances, while a small number of works were validated by real-world data from industrial firms, of which the most popular are sawmills, wood and furniture, automobile and semiconductors and electronic devices.This study has been funded by the Universitat Politècnica de València projects: ‘Material Requirement Planning Fourth Generation (MRPIV)’ (Ref. PAID-05-12) and ‘Quantitative Models for the Design of Socially Responsible Supply Chains under Uncertainty Conditions. Application of Solution Strategies based on Hybrid Metaheuristics’ (PAID-06-12).Díaz-Madroñero Boluda, FM.; Mula, J.; Peidro Payá, D. (2014). A review of discrete-time optimization models for tactical production planning. International Journal of Production Research. 52(17):5171-5205. doi:10.1080/00207543.2014.899721S51715205521

Taxiway Aircraft Traffic Scheduling: A Model and Solution Algorithms

With the drastic increase in the demand for air travel, taxiway aircraft traffic scheduling is becoming increasingly important in managing air traffic. In order to reduce traffic congestion on taxiways, this thesis proposes a tool for air traffic controllers to use in decision making: a taxiway air traffic model developed using Mixed Integer Programming (MIP) that can be applied to a rolling time horizon. The objective of this model is to minimize the total taxi time, and the output is a schedule and route for each aircraft. This MIP model assumes that only the origin and destination of each aircraft is fixed; due to some uncertain factors in the air arrival and departure process, it allows for the departure time and arrival time to vary within a certain time window. This MIP model features aircraft type, and also incorporates runway crossings and runway separations. The model is programmed using C++ and Solved in CPLEX 12.1. Runways 26R and 26L of George Bush International Airport are used to find solutions. The author presents a rolling horizon method by dividing the large scheduling issue into smaller time interval problems according to the scheduled times of departure or arrival. A bound is also proposed based on the discretized time interval problems. By using partial data from George Bush International Airport (IAH), solutions are obtained. The results are compared with the bound and show fairly high optimality. Compared with the previous research, this thesis presents a model with more flexibility by considering different operations. By using the rolling horizon method, the problem is broken into smaller units that can be solved efficiently without losing much optimality

Uma ferramenta de decisão para um problema de Route Scheduling e Crew Assignment

Estágio orientado na empresa, pelo Eng. Nuno Filipe Correia de Melo Ferreira de AlmeidaTese de mestrado integrado. Engenharia Industrial e Gestão. Faculdade de Engenharia. Universidade do Porto. 201