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

Solving Lotsizing Problems on Parallel Identical Machines Using Symmetry Breaking Constraints

Production planning on multiple parallel machines is an interesting problem, both from a theoretical and practical point of view. The parallel machine lotsizing problem consists of finding the optimal timing and level of production and the best allocation of products to machines. In this paper we look at how to incorporate parallel machines in a Mixed Integer Programming model when using commercial optimization software. More specifically, we look at the issue of symmetry. When multiple identical machines are available, many alternative optimal solutions can be created by renumbering the machines. These alternative solutions lead to difficulties in the branch-and-bound algorithm. We propose new constraints to break this symmetry. We tested our approach on the parallel machine lotsizing problem with setup costs and times, using a network reformulation for this problem. Computational tests indicate that several of the proposed symmetry breaking constraints substantially improve the solution time, except when used for solving the very easy problems. The results highlight the importance of creative modeling in solving Mixed Integer Programming problems.Mixed Integer Programming;Formulations;Symmetry;Lotsizing

Dynamic Multi-Product Multi-Facility Supply Network Design

Volatile Märkte, sich verkürzende Produktlebenszyklen und der globale Wettbewerb stellen die klassischen Lieferketten vor große Herausforderungen. Supply Chains müssen sich kurzfristig und dynamisch an die volatilen Marktanforderungen anpassen. Die volatilen Märkte werden immer weniger vorhersehbar. Die Supply Chains selbst müssen dynamischer werden, um die Marktvolatilität zu bewältigen. Daher wandelt sich das klassische Bild der stabilen Supply Chain in ein dynamisches Supply Network-Verständnis. Um diese neuen Anforderungen abzudecken, schlägt diese Arbeit das Dynamic Supply Network Design Problem (DSNDP) als zentrales Instrument in hierarchischen Planungssystemen vor. Zentrales Ziel der Arbeit ist es, einen Ansatz für das Design dynamischer Supply Networks unter gegebenen physischen Randbedingungen bereitzustellen. Um dieses Ziel zu erreichen, wird das Problem zunächst motiviert, charakterisiert und in Beziehung zum Stand der Technik der Supply Chain Planungsansätze gesetzt. Nachdem diese Grundlage geschaffen ist, wird das Problem formalisiert. Dazu werden alle Modellierungsannahmen formuliert. Auf dieser Grundlage werden drei aufeinander aufbauende Optimierungsmodelle für das DSNDP entwickelt, wobei ein Mixed Integer Linear Programming (MILP) Ansatz verwendet wird. Die Optimierungsmodelle entwerfen ein dynamisches Supply Network durch die Entwicklung eines Qualifizierungsplans für alle verfügbaren Ressourcen in jeder Periode des Planungshorizonts. Dieses dynamische Supply Network weist den verfügbaren kapazitiven Ressourcen die entsprechenden Qualifikationen zu, um die volatile Nachfrage dynamisch zu bedienen und die Gesamtkosten zu minimieren. Dabei werden der tatsächliche Produktionsschwerpunkt jedes Produktionspartners (Produktmix-Abhängigkeit), die spezifischen Erfahrungen jedes Produktionspartners (Qualifizierungsabstufung), die Fähigkeit der Fabriken, ein Produktportfolio und nicht nur einzelne Produkte abzudecken (multitasking facility) sowie die Möglichkeit der Pre-Prozessierung berücksichtigt. Jedes Modell wird um eine dieser Hauptannahmen erweitert. Dies macht die Modelle immer realistischer jedoch auch komplexer. Einschränkungen in der Problemgröße motivieren die Arbeit zu einem zusätzlichen heuristischen Ansatz. Die vorgeschlagene Displacement Heuristik berücksichtigt die gleichen Annahmen, löst das Designproblem jedoch iterativ. Dadurch erreicht sie zwar niedrige Berechnungszeiten, verliert aber die Optimalitätsgarantie. Durch die geringen Rechenzeiten ist die Heuristik für realistische industrielle Problemstellungen geeignet. Die Displacement Heuristik führt zu Optimalitätslücken von 4 bis 6%, wie die Validierung gegen das Optimierungsmodell zeigt. Mit spezifischen Experimenten wird das Verhalten der Displacement-Heuristik in realistischen industriellen Problemstellungen evaluiert. Aus den Erkenntnissen dieser Auswertung lassen sich mehrere konkrete Vorschläge für die Gestaltung und das Management dynamischer Supply Networks ableiten. Da der Trend zu Volatilität und kürzeren Produktlebenszyklen anhält, ist zum Abschluss dieser Arbeit eine Motivation für weitere Forschungs- und Umsetzungsaktivitäten auf dem Gebiet der dynamischen Wertschöpfungsnetzgestaltung gegeben

Modelling an End to End Supply Chain system Using Simulation

Within the current uncertain environment industries are predominantly faced with various challenges resulting in greater need for skilled management and adequate technique as well as tools to manage Supply Chains (SC) efficiently. Derived from this observation is the need to develop a generic/reusable modelling framework that would allow firms to analyse their operational performance over time (Mackulak and Lawrence 1998, Beamon and Chen 2001, Petrovic 2001, Lau et al. 2008, Khilwani et al. 2011, Cigollini et al. 2014). However for this to be effectively managed the simulation modelling efforts should be directed towards identifying the scope of the SC and the key processes performed between players. Purpose: The research attempts to analyse trends in the field of supply chain modelling using simulation and provide directions for future research by reviewing existing Operations Research/Operations Management (OR/OM) literature. Structural and operational complexities as well as different business processes within various industries are often limiting factors during modelling efforts. Successively, this calls for the end to end (E2E) SC modelling framework where the generic processes, related policies and techniques could be captured and supported by the powerful capabilities of simulation. Research Approach: Following Mitroff’s (1974) scientific inquiry model and Sargent (2011) this research will adopt simulation methodology and focus on systematic literature review in order to establish generic OR processes and differentiate them from those which are specific to certain industries. The aim of the research is provide a clear and informed overview of the existing literature in the area of supply chain simulation. Therefore through a profound examination of the selected studies a conceptual model will be design based on the selection of the most commonly used SC Processes and simulation techniques used within those processes. The description of individual elements that make up SC processes (Hermann and Pundoor 2006) will be defined using building blocks, which are also known as Process Categories. Findings and Originality: This paper presents an E2E SC simulation conceptual model realised through means of systematic literature review. Practitioners have adopted the term E2E SC while this is not extensively featured within academic literature. The existing SC studies lack generality in regards to capturing the entire SC within one methodological framework, which this study aims to address. Research Impact: A systematic review of the supply chain and simulation literature takes an integrated and holistic assessment of an E2E SC, from market-demand scenarios through order management and planning processes, and on to manufacturing and physical distribution. Thus by providing significant advances in understanding of the theory, methods used and applicability of supply chain simulation, this paper will further develop a body of knowledge within this subject area. Practical Impact: The paper will empower practitioners’ knowledge and understanding of the supply chain processes characteristics that can be modelled using simulation. Moreover it will facilitate a selection of specific data required for the simulation in accordance to the individual needs of the industry

Two-echelon freight transport optimisation: unifying concepts via a systematic review

Multi-echelon distribution schemes are one of the most common strategies adopted by the transport companies in an aim of cost reduction, but their identification in scientific literature is not always easy due to a lack of unification. This paper presents the main concepts of two-echelon distribution via a systematic review, in the specific a meta-narrative analysis, in order to identify and unify the main concepts, issues and methods that can be helpful for scientists and transport practitioners. The problem of system cost optimisation in two-echelon freight transport systems is defined. Moreover, the main variants are synthetically presented and discussed. Finally, future research directions are proposed.location-routing problems, multi-echelon distribution, cross-docking, combinatorial optimisation, systematic review.

A hierarchical approach to multi-project planning under uncertainty

We survey several viewpoints on the management of the planning complexity of multi-project organisations under uncertainty. A positioning framework is proposed to distinguish between different types of project-driven organisations, which is meant to aid project management in the choice between the various existing planning approaches. We discuss the current state of the art of hierarchical planning approaches both for traditional manufacturing and for project environments. We introduce a generic hierarchical project planning and control framework that serves to position planning methods for multi-project planning under uncertainty. We discuss multiple techniques for dealing with the uncertainty inherent to the different hierarchical stages in a multi-project organisation. In the last part of this paper we discuss two cases from practice and we relate these practical cases to the positioning framework that is put forward in the paper

Hierarchical Planning Methodology for a Supply Chain Management

Hierarchical production planning is a widely utilized methodology for real world capacitated production planning systems with the aim of establishing different decision–making levels of the planning issues on the time horizon considered. This paper presents a hierarchical approach proposed to a company that produces reusable shopping bags in Chile and Perú, to determine the optimal allocation of resources at the tactical level as well as over the most immediate planning horizon to meet customer demands for the next weeks. Starting from an aggregated production planning model, the aggregated decisions are disaggregated into refined decisions in two levels, using a couple of optimization models that impose appropriate constraints to keep coherence of the plan on the production system. The main features of the hierarchical solution approach are presented

Solving Lotsizing Problems on Parallel Identical Machines Using Symmetry Breaking Constraints

Production planning on multiple parallel machines is an interesting problem, both from a theoretical and practical point of view. The parallel machine lotsizing problem consists of finding the optimal timing and level of production and the best allocation of products to machines. In this paper we look at how to incorporate parallel machines in a Mixed Integer Programming model when using commercial optimization software. More specifically, we look at the issue of symmetry. When multiple identical machines are available, many alternative optimal solutions can be created by renumbering the machines. These alternative solutions lead to difficulties in the branch-and-bound algorithm. We propose new constraints to break this symmetry. We tested our approach on the parallel machine lotsizing problem with setup costs and times, using a network reformulation for this problem. Computational tests indicate that several of the proposed symmetry breaking constraints substantially improve the solution time, except when used for solving the very easy problems. The results highlight the importance of creative modeling in solving Mixed Integer Programming problems

Integrated stochastic distribution network design: a two-level facility location problem with applications to maize crops transportation in Tanzania

thesis submitted to the Faculty of Science in fulfilment of the requirements for the degree of Doctor of Philosophy. March 17, 2015.A two-level facility location problem (FLP) arose in the transport network of maize crop in Tanzania has been studied. The three layers, namely, production centers (PCs), distribution centers (DCs) and customer points (CPs) are considered in the two-level FLP. The stochastic e ect on the two-level FLP due to rainfall in the network links, between the DCs and CPs, has been studied. The ow of maize crop from PCs to CPs through DCs is designed at a minimum cost under deterministic and stochastic scenarios. The three decisions made simultaneously are: to determine the locations of DCs (including number of DCs), allocation of CPs to the selected DCs, allocation of selected DCs to PCs, and to determine the amount of maize crop transported from PCs to DCs and then from DCs to CPs. We have modelled the problem and generate results by optimizing the model with respect to optimal location-allocation strategies. We have considered two networks, the existing network and an extended network. In the existing network there are four PCs, ve DCs and ninety three CPs. In the extended network three additional DCs are considered. For the modelling purpose we have used the rainfall data from 2007 - 2010 in each week for 17 weeks. The optimized results for the existing network have shown improvements in cost saving compared to the manually operated existing network. In the extended network, the results have shown much more e cient and cost saving distribution system compared to the results of the existing network