Integration of production planning and scheduling: Overview, challenges and opportunities

Maravelias, Christos T.; Sung, Charles

doi:10.1016/j.compchemeng.2009.06.007

Cited by 326 publications

(197 citation statements)

References 89 publications

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“…There have been numerous studies to develop efficient operation control systems, and such research goes well back in time [3][4][5][6][7][8][9]. However, studies of operation control in woodworking business are rather few, and those available fail to exhaustively cover the capability of today's information technologies and production control system simulation methods.…”

Section: Introductionmentioning

confidence: 99%

Simulating operational control of production in lumber house building businesses

Korolchenko

Pizhurin

2017

MATEC Web Conf.

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Abstract. Substantial reserves for higher operation efficiency in wooden house building businesses exist in improvements of production control system through methods of simulation and optimization. This report presents analysis of key factors of lumber house building processes that influence approaches to production control simulation. The need to factor in interconnection and dependence of lumber and house part production processes is highly difficult for operational control of the production system in question. The optimization mathematical models that we developed will help to solve the tasks of operational scheduling at all stages of wooden house manufacturing, from log cutting to production of finished assembly sets.

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Section: Introductionmentioning

confidence: 99%

Simulating operational control of production in lumber house building businesses

Korolchenko

Pizhurin

2017

MATEC Web Conf.

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“…However, the integration of planning and scheduling remains an open problem. Maravelias and Sung (2009) have recently published a review paper on this topic. Garcia and You (2015) identify the challenges in dealing with multilevel systems, modeling, optimization, uncertainty handling, and efficient algorithms design.…”

Section: Introductionmentioning

confidence: 99%

Perspectives in multilevel decision-making in the process industry

Brunaud¹,

Grossmann²

2017

Front. Eng

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Decisions in supply chains are hierarchically organized. Strategic decisions involve the long-term planning of the structure of the supply chain network. Tactical decisions are mid-term plans to allocate the production and distribution of materials, while operational decisions are related to the daily planning of the execution of manufacturing operations. These planning processes are conducted independently with minimal exchange of information between them. Achieving a better coordination between these processes allows companies to capture benefits that are currently out of their reach and improve the communication among their functional areas. We propose a network representation for the multilevel decision structure and analyze the components that are involved in finding integrated solutions that maximize the sum of the benefits of all nodes of the decision network. Although such task is very challenging, significant research progress has been made in each component of this structure. An overview of strategic models, mid-term planning models, and scheduling models is presented to address the solution of each node in the decision network. Coordination mechanisms for converging the integrated solutions are also analyzed, including solving large-scale models, multiobjective optimization, bi-level programming, and decomposition. We conclude by summarizing the challenges that hinder the full integration of multilevel decision making in supply chain management.

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“…Lagrangean Decomposition, a particular case of Lagrangean Relaxation [18], has also been investigated by [19] who decomposed their planning problem temporally and spatially in order to solve large instances. A review of methods and decomposition approaches for the integration of planning and scheduling can be found in the work by [20].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Bilevel-Lagrangean Decomposition Scheme for the Integration of Planning and Scheduling of a Network of Batch Plants

Calfa

Agarwal

Grossmann

et al. 2013

Ind. Eng. Chem. Res.

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Motivated by a real-world industrial problem, this work deals with the integration of planning and scheduling in the operation of a network of batch plants. The network consists of single-stage, multiproduct batch plants located in different sites, which can exchange intermediate products in order to blend them to obtain finished products. The time horizon is given and divided into multiple time periods, at the end of which the customer demands have to be exactly satisfied. The planning model is a simplified and aggregate formulation derived from the detailed precedence-based scheduling formulation. Traveling Salesman Problem (TSP) constraints are incorporated at the planning level in order to predict the sequence-dependent changeovers between groups of products, within and across time periods, without requiring the detailed timing of operations, which is performed at the scheduling level. In an effort to avoid solving the full-space, rigorous scheduling model, especially for large problem sizes, two decomposition strategies are investigated: Bilevel and Temporal Lagrangean. We demonstrate that Bilevel Decomposition is efficient for small to medium problem instances and that further decomposition of the planning problem, yielding a hybrid decomposition scheme, is advantageous for tackling a large-scale industrial test case. ysl ill t 0-1 variable to force only one plant l to ship product i to customer l at time period t Notation Planning Model Variablesyg gult 0-1 variable to denote the assignment of group g to unit u of plant l at time period t ygf gult 0-1 variable to denote the first group g assigned to unit u of plant l at time period t ygl gult 0-1 variable to denote the last group g assigned to unit u of plant l at time period t yp iult 0-1 variable to denote the assignment of product i to unit u of plant l at time period t zg gg ult 0-1 variable to denote if group g is followed by group g in unit u of plant l within time period t zzg gg ult 0-1 variable to denote if link between group g and group g in unit u of plant l within time period t is broken zzzg gg ult 0-1 variable to denote a changeover between group g and group g in unit u of plant l across time period t Unit-Specific General Precedence Model VariablesT e iult End time of product i in unit u of plant l at time period t T s iult Start time of product i in unit u of plant l at time period t 4 wp ii ult 0-1 variable to denote changeover between product i and product i in unit u of plant l across time period t xp ii ult 0-1 variable to denote local precedence between product i and product i in unit u of plant l within time period t yp iult 0-1 variable to denote the assignment of product ito unit u of plant l at time period t ypf iult 0-1 variable to denote the first product i assigned to unit u of plant l at time period t ypl iult 0-1 variable to denote the last product i assigned to unit u of plant l at time period t zp ii ult 0-1 variable to denote global precedence between product i and product i in unit u of plant l within time period t

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Integration of production planning and scheduling: Overview, challenges and opportunities

Cited by 326 publications

References 89 publications

Simulating operational control of production in lumber house building businesses

Simulating operational control of production in lumber house building businesses

Perspectives in multilevel decision-making in the process industry

Hybrid Bilevel-Lagrangean Decomposition Scheme for the Integration of Planning and Scheduling of a Network of Batch Plants

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