10,035 research outputs found
Lotsizing and scheduling in the glass container industry
Manufacturing organizations are keen to improve their competitive position in the global marketplace by increasing operational performance. Production planning is crucial to this end and represents one of the most challenging tasks managers are facing today. Among a large number of alternatives, production planning processes help decision-making by tradingoff conflicting objectives in the presence of technological, marketing and financial constraints.Two important classes of such problems are lotsizing and scheduling. Proofs from complexity theory supported by computational experiments clearly show the hardness of solving lotsizing and scheduling problems.Motivated by a real-world case, the glass container industry production planning and scheduling problem is studied in depth. Due to its inherent complexity and to the frequent interdependencies between decisions that are made at and affect different organizational echelons, the system is decomposed into a two-level hierarchically organized planning structure: long-term and short-term levels.This dissertation explores extensions of lotsizing and scheduling problems that appear in both levels. We address these variants in two research directions. On one hand, we develop and implement different approaches to obtain good quality solutions, as metaheuristics (namely variable neighborhood search) and Lagrangian-based heuristics, as well as other special-purpose heuristics. On the other hand, we try to combine new stronger models and valid inequalities based on the polyhedral structure of these problems to tighten linear relaxations and speed up the solution process.Manufacturing organizations are keen to improve their competitive position in the global marketplace by increasing operational performance. Production planning is crucial to this end and represents one of the most challenging tasks managers are facing today. Among a large number of alternatives, production planning processes help decision-making by tradingoff conflicting objectives in the presence of technological, marketing and financial constraints.Two important classes of such problems are lotsizing and scheduling. Proofs from complexity theory supported by computational experiments clearly show the hardness of solving lotsizing and scheduling problems.Motivated by a real-world case, the glass container industry production planning and scheduling problem is studied in depth. Due to its inherent complexity and to the frequent interdependencies between decisions that are made at and affect different organizational echelons, the system is decomposed into a two-level hierarchically organized planning structure: long-term and short-term levels.This dissertation explores extensions of lotsizing and scheduling problems that appear in both levels. We address these variants in two research directions. On one hand, we develop and implement different approaches to obtain good quality solutions, as metaheuristics (namely variable neighborhood search) and Lagrangian-based heuristics, as well as other special-purpose heuristics. On the other hand, we try to combine new stronger models and valid inequalities based on the polyhedral structure of these problems to tighten linear relaxations and speed up the solution process
Production planning and scheduling optimization model: a case of study for a glass container company
Based on a case study, this paper deals with the production planning and scheduling problem of the glass con-tainer industry. This is a facility production system that has a set of furnaces where the glass is produced in order to meet the demand, being afterwards distributed to a set of parallel molding machines. Due to huge setup times involved in a color changeover, manufacturers adopt their own mix of furnaces and machines to meet the needs of their customers as flexibly and efficiently as possible. In this paper we proposed an optimization model that maximizes the fulfillment of the demand considering typical constraints from the planning production formulation as well as real case production constraints such as the limited product changeovers and the minimum run length in a machine. The complexity of the proposed model is assessed by means of an industrial real life problem
Industrial insights into lot sizing and schedulingmodeling
© 2015 Brazilian Operations Research Society. Lot sizing and scheduling by mixed integer programming has been a hot research topic inthe last 20 years. Researchers have been trying to develop stronger formulations, as well as to incorporatereal-world requirements from different applications. This paper illustrates some of these requirements anddemonstrates how small- and big-bucket models have been adapted and extended. Motivation comes fromdifferent industries, especially from process and fast-moving consumer goods industries
Defragmenting the Module Layout of a Partially Reconfigurable Device
Modern generations of field-programmable gate arrays (FPGAs) allow for
partial reconfiguration. In an online context, where the sequence of modules to
be loaded on the FPGA is unknown beforehand, repeated insertion and deletion of
modules leads to progressive fragmentation of the available space, making
defragmentation an important issue. We address this problem by propose an
online and an offline component for the defragmentation of the available space.
We consider defragmenting the module layout on a reconfigurable device. This
corresponds to solving a two-dimensional strip packing problem. Problems of
this type are NP-hard in the strong sense, and previous algorithmic results are
rather limited. Based on a graph-theoretic characterization of feasible
packings, we develop a method that can solve two-dimensional defragmentation
instances of practical size to optimality. Our approach is validated for a set
of benchmark instances.Comment: 10 pages, 11 figures, 1 table, Latex, to appear in "Engineering of
Reconfigurable Systems and Algorithms" as a "Distinguished Paper
Advanced Planning Concepts in the Closed-Loop Container Network of ARN
In this paper we discuss a real-life case study in the optimization of the logistics network for the collection of containers from end-of-life vehicle dismantlers in the Netherlands.Advanced planning concepts like dynamic assignment of dismantlers to logistic service providers are analyzed by a simulation model.In this model, we periodically solve a vehicle routing problem to gain insight in the long-term performance of the system.The vehicle routing problem considered is a multi depot pickup and delivery problem with alternative delivery locations.We solve this problem with a heuristic based on route generation and set partitioning.Reverse logistics;Closed-loop supply chain mmanagement;vehicle routing;set partitioning;distribution planning
Supply chain management and the Romanian transition
The purpose of this paper is to perform a systemic analysis of the Supply Chain Management, and to show what are the essential aspects of such a complex process. Actually, it is an integral perspective of intra- and interorganizational management activities aiming at the optimization of all important tangible and intangible fluxes and forces acting in a multifield framework. In the same time, we are looking at the Romanian transition and show how such a new perspective can be applied to the business environment. The analysis is challenging, since Romania is in a deep change process from a centrally planned economy toward a free market economy.management, supply chain management, system analysis, transition economy.
Cargo/Logistics Airlift System Study (CLASS), Volume 2
Air containerization is discussed in terms of lower freight rates, size and pallet limitations, refrigeration, backhaul of empties, and ownership. It is concluded that there is a need for an advance air cargo system as indicated by the industry/transportation case studies, and a stimulation of the air cargo would result in freight rate reductions
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