Robust planning: a new paradigm for demand chain planning

Landeghem, Hendrik Van; Vanmaele, Hendrik

doi:10.1016/s0272-6963(02)00039-6

Cited by 171 publications

(77 citation statements)

References 22 publications

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“…The main difficulties of stochastic programming approach are: (a) lack of existence of distribution function of data and (b) computational challenges [25].The concept and advantages of robust approach in general, and in supply chain planning in particular, can be illustrated in Figure 1. Deterministic approaches obtain the solution based on averaging or "good guess".…”

Section: Methodology Of Robust-fuzzymentioning

confidence: 99%

Robust-fuzzy model for supplier selection under uncertainty: An application to the automobile industry

2017

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This paper proposes an innovative robust-fuzzy method for multi-objective, multi-period supplier selection problem under multiple uncertainties. This approach integrates robust optimization and fuzzy programming. Uncertain parameters are modeled as random variables that take value within a symmetrical interval. However, due to the complexity or ambiguity of some real world problems and specially the nature of some of the available input data, the length of interval is also highly uncertain. This ambiguity motivated us to present a new approach, which can be applicable to multiple uncertainties conditions. Thus, in our approach the half-length of these intervals is also represented by fuzzy membership function. We develop a model and a solution approach to select suppliers by considering risk. The proposed method is applied to a real case of supplier selection in automobile industry under uncertainty and ambiguity conditions. To verify the proposed model, we evaluated the results by simulation technique and compared values of objective function under different scenarios.

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Section: Methodology Of Robust-fuzzymentioning

confidence: 99%

Robust-fuzzy model for supplier selection under uncertainty: An application to the automobile industry

2017

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“…Sodhi (2003) and Van Landeghem and Vanmaele (2002) argue that tactical planning encompasses determining how much should be produced in which production plant and when, with planning horizon about months or weeks. This calls for an extensive information sharing with suppliers and integrating them in the planning process.…”

Section: Supply Chain Planningmentioning

confidence: 99%

Developing a Framework for Supply Chain Planning in Construction

Thunberg¹

2016

Linköping Studies in Science and Technology. Dissertations

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Supply chain management (SCM) has been stressed as a remedy to many of the underlying issues in the construction industry. However, the positive examples where SCM has been successfully utilised and diminished the lingering issues in construction is scarce. The question is why. Previous studies have stressed the importance of planning both the construction project as such but also the supply chain and the logistics. As an important part of SCM, supply chain planning (SCP) focuses on planning different aspects of the supply chain through involving different members of the supply chain in the planning process. SCP in construction is scarce as the planning of the logistics in general. Failing to plan the supply chain, involving supply chain members in the planning, and integrating the processes of planning the supply chains and the construction project can be one reason for the low numbers of successful SCM adoption in construction. In improving the SCP in construction, this thesis develops a SCP framework for construction that involves the main contractor, subcontractors, and suppliers. The aim is to improve SCP, collaboration, and eliminate many of the common problems in construction through a SCM and SCP perspective.The developed framework is based on an existing planning framework for sales and operations planning. This framework is generic and synthesises planning in general. It consists of identifying/developing: outcomes, input, organisation, process, key performance measurements, and IT-tools. It is thus necessary to investigate what these aspects means in a construction context. Four research objects will be fulfilled: The first objective will aid in focusing the work with developing the framework as one aim of the framework is to aid in eliminating common logistical problems. In doing so it is needed to identify what problems exist and how the SCP framework can aid in overcoming them. The second and third objective focus on developing the framework in terms of developing a planning process (procedure) and an organisation for developing the plans. These two also includes identifying outcomes of SCP and important inputs. The final objective focus on suggesting important performance measurements for aiding in the planning process.Several different studies have aid in fulfilling the objectives and the purpose. A case study, literature review, and a series of interviews aided in fulfilling objective 1. The interview series and focus groups were used for fulfilling objectives 2 and 3. Objective 4 used the results from the case study. Through logical reasoning and compiling the previous works made it possible to finalise and develop the framework.Findings indicate that common logistical problems can be categorised as: material flow issues, internal company communication, project communication, and complexity. The first one contains problems with e.g. delivery reliability, material flows, and inventories. Company communication regards problems with e.g. sharing information internally, not updating plans, ...

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“…One potential system which could be used is the Beer game system, which has previously been used to study the dynamic behaviour of production-distribution systems (Van Landeghem and Vanmaele, 2002;O'Donnell et al, 2006), but not specifically rogue seasonality.…”

Section: Relevant Studies On Rogue Seasonalitymentioning

confidence: 99%

Rogue seasonality in supply chains: an investigation and a measurement approach

Shukla

Naim

2015

Journal of Manufacturing Technology Management

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Purpose -Shukla et al (2012) proposed a signature and index to detect and measure rogue seasonality in supply chains, but which however, were not effectively validated. The authors have sought to investigate rogue seasonality using control theory and realistic multi echelon systems and rigorously validate these measures, so as to enable their application in practice. The paper aims to discuss these issues.Design/methodology/approach -Frequency domain analysis of single echelon and simulated four echelon Beer game system outputs are used in the investigation, with the simulation incorporating realistic features such as non-linearities from backlogs and batching, hybrid make to order-make to stock ordering system and the shipment variable. Lead time, demand process parameters, ordering parameters and batch size are varied in the simulation to rigorously assess the validity of the index.Findings -The signature based on the cluster profiles of variables, specifically whether the variables cluster together with or away from exogenous demand, was validated. However, a threshold for the proportion of variables that could be clustered with exogenous demand and the system still being classified as exhibiting rogue seasonality, would require to be specified. The index, which is derived by quantifying the cluster profile relationships, was found to be a valid and robust indicator of the intensity of rogue seasonality, and which did not need any adjustments of the kind discussed for the signature. The greater effectiveness of the frequency domain in comparison to time for deriving the signature and index was demonstrated.Practical implications -This work enables speedy assessment of rogue seasonality in supply chains which in turn ensures appropriate and timely action to minimize its adverse consequences.Originality/value -Detailed and specific investigation on rogue seasonality using control theory and Beer game simulation and rigorous validation of the signature and index using these methods.

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Robust planning: a new paradigm for demand chain planning

Cited by 171 publications

References 22 publications

Robust-fuzzy model for supplier selection under uncertainty: An application to the automobile industry

Robust-fuzzy model for supplier selection under uncertainty: An application to the automobile industry

Developing a Framework for Supply Chain Planning in Construction

Rogue seasonality in supply chains: an investigation and a measurement approach

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