1,287 research outputs found
Single Item Lot Sizing Problem for a Warm/Cold Process with Immediate Lost Sales
Cataloged from PDF version of article.We consider the dynamic lot-sizing problem with finite capacity and possible lost sales for a process that could be kept
warm at a unit variable cost for the next period t + 1 only if more than a threshold value Qt has been produced and would
be cold, otherwise. Production with a cold process incurs a fixed positive setup cost, Kt and setup time, St, which may be
positive. Setup costs and times for a warm process are negligible. We develop a dynamic programming formulation of the
problem, establish theoretical results on the structure of the optimal production plan in the presence of zero and positive
setup times with Wagner–Whitin-type cost structures. We also show that the solution to the dynamic lot-sizing problem
with lost sales are generated from the full commitment production series improved via lost sales decisions in the presence of
a warm/cold process.
2006 Elsevier B.V. All rights reserved
An optimization framework for solving capacitated multi-level lot-sizing problems with backlogging
This paper proposes two new mixed integer programming models for capacitated multi-level lot-sizing problems with backlogging, whose linear programming relaxations provide good lower bounds on the optimal solution value. We show that both of these strong formulations yield the same lower bounds. In addition to these theoretical results, we propose a new, effective optimization framework that achieves high quality solutions in reasonable computational time. Computational results show that the proposed optimization framework is superior to other well-known approaches on several important performance dimensions
Confidence-based Reasoning in Stochastic Constraint Programming
In this work we introduce a novel approach, based on sampling, for finding
assignments that are likely to be solutions to stochastic constraint
satisfaction problems and constraint optimisation problems. Our approach
reduces the size of the original problem being analysed; by solving this
reduced problem, with a given confidence probability, we obtain assignments
that satisfy the chance constraints in the original model within prescribed
error tolerance thresholds. To achieve this, we blend concepts from stochastic
constraint programming and statistics. We discuss both exact and approximate
variants of our method. The framework we introduce can be immediately employed
in concert with existing approaches for solving stochastic constraint programs.
A thorough computational study on a number of stochastic combinatorial
optimisation problems demonstrates the effectiveness of our approach.Comment: 53 pages, working draf
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).DÃaz-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
Integrated Production and Distribution planning of perishable goods
Tese de doutoramento. Programa Doutoral em Engenharia Industrial e Gestão. Faculdade de Engenharia. Universidade do Porto. 201
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