Planning and scheduling of the make-and-pack dairy production under lifetime uncertainty

Sel, Çağrı; Bilgen, Bilge; Bloemhof-Ruwaard, Jacqueline

doi:10.1016/j.apm.2017.06.002

Cited by 25 publications

(9 citation statements)

References 45 publications

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“…Doganis and Sarimveis [101] solved the scheduling problem of a single yoghurt production line taking into account inventory, manpower and capacity restrictions. The model was tested using data from a yoghurt production line of a Greek dairy industry, where 18 products were produced and global optimum schedules have been generated in less than 15 s. The integrated planning and scheduling problem of a small size Balkan type semi-continuous yoghurt facility, with eight final product types, produced by three intermediates has also been investigated [102]. The evaluation of the proposed MILP approach has been utilized via a simulation model.…”

Section: Food Industriesmentioning

confidence: 99%

Optimization-Based Scheduling for the Process Industries: From Theory to Real-Life Industrial Applications

2019

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Scheduling is a major component for the efficient operation of the process industries. Especially in the current competitive globalized market, scheduling is of vital importance to most industries, since profit margins are miniscule. Prof. Sargent was one of the first to acknowledge this. His breakthrough contributions paved the way to other researchers to develop optimization-based methods that can address a plethora of process scheduling problems. Despite the plethora of works published by the scientific community, the practical implementation of optimization-based scheduling in industrial real-life applications is limited. In most industries, the optimization of production scheduling is seen as an extremely complex task and most schedulers prefer the use of a simulation-based software or manual decision, which result to suboptimal solutions. This work presents a comprehensive review of the theoretical concepts that emerged in the last 30 years. Moreover, an overview of the contributions that address real-life industrial case studies of process scheduling is illustrated. Finally, the major reasons that impede the application of optimization-based scheduling are critically analyzed and possible remedies are discussed.

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Section: Food Industriesmentioning

confidence: 99%

Optimization-Based Scheduling for the Process Industries: From Theory to Real-Life Industrial Applications

2019

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“…The first approach focuses on the definition of the best process options either by optimizing production scheduling (i.e. time management) (Sel et al, 2017) by comparing multiple process scenarios on the basis of several criteria (Gésan-Guiziou et al, 2019;Depping et al, 2017Depping et al, , 2020. In these studies, the operating conditions and process design of each unit operations, combined in the overall process, have been considered as constant.…”

Section: Introductionmentioning

confidence: 99%

Formulating multiobjective optimization of 0.1 μm microfiltration of skim milk

Belna

Ndiaye

Taillandier

et al. 2020

Food and Bioproducts Processing

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Optimizing 0.1 m microfiltration (MF) of skim milk requires formulating optimization of a food processing problem with conflicting objectives that consider product composition, process variables and operating conditions. Formulating the MF optimization problem requires knowledge from experts about food processing, dairy product production and equipment manufacturing. This study formulated the MF optimization problem in an innovative manner: as a multiobjective optimization problem that considered the entire MF process. Eleven experts were interviewed to identify the knowledge domains necessary, which required 36 interviews over a total of 14 h. Formulation was achieved from the MF process to the compositions of the permeate and retentate fractions. Five conflicting optimization objectives, influenced by 36 variables, were set up to formulate the problem. Five of the variables were decision variables used to control the MF, and the other 31 were intermediate calculation variables. This approach opens new perspectives for optimization of food processes that integrate expert knowledge.

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“…Although general scheduling problems with uncertainty have been considered by several authors (Lusa et al, 2008;Galetakis et al, 2012;El Amraoui and Mesghouni, 2014;Hu and Hu, 2016;Kenan et al, 2017;Sel et al, 2017), there has been limited work on HEN cleaning scheduling under uncertainty. A search through the literature found a few publications, such as Bagajewicz (2004a, 2005).…”

Section: Introductionmentioning

confidence: 99%

Optimisation of heat exchanger network cleaning schedules: Incorporating uncertainty in fouling and cleaning model parameters

Ismaili

Lee

Wilson

et al. 2019

Computers & Chemical Engineering

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The optimisation of the cleaning schedule in heat exchanger networks (HENs) subject to fouling is presented in which the impact of parametric uncertainty is considered. This work is based on the realisation that these HEN cleaning scheduling problems are multistage mixedinteger optimal control problems (MIOCPs) in which the controls, i.e. cleaning actions, exhibit bang-bang behaviour as they occur linearly in the system equations. A multiple scenario feasible path MIOCP approach is proposed, whereby many scenarios of the HEN multiperiod problem are stacked, sharing the same control actions. This is implemented on a 10 unit and a 25 unit HEN case studies representing crude oil refinery preheat trains (PHTs). Results show that there is a large difference in financial performance for the deterministic case versus the parametric uncertainty problem and hence it is vital that uncertainty be taken into account during the optimisation of schedules for HEN maintenance problems.

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Planning and scheduling of the make-and-pack dairy production under lifetime uncertainty

Cited by 25 publications

References 45 publications

Optimization-Based Scheduling for the Process Industries: From Theory to Real-Life Industrial Applications

Optimization-Based Scheduling for the Process Industries: From Theory to Real-Life Industrial Applications

Formulating multiobjective optimization of 0.1 μm microfiltration of skim milk

Optimisation of heat exchanger network cleaning schedules: Incorporating uncertainty in fouling and cleaning model parameters

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