Overview of Scheduling and Planning of Batch Process Operations

Reklaitis, Gintaras V.

doi:10.1007/978-3-642-60972-5_27

Cited by 119 publications

(105 citation statements)

References 47 publications

Supporting

Mentioning

102

Contrasting

Unclassified

Order By: Relevance

“…Constraints (13)(14)(15) impose the rules for the starting time of each job on each machine; while, as mentioned above, equality (12) gives the completion time of each job on the last machine as a function of its start time and its processing time. Constraint (13) says that between the starting times of consecutive jobs on a machine, there must be enough time for the first (of the two jobs) to be processed.…”

Section: Milp Models For Flowshop With Unlimited Buffermentioning

confidence: 99%

“…Constraint (13) says that between the starting times of consecutive jobs on a machine, there must be enough time for the first (of the two jobs) to be processed. Constraint (14) indicates that between the starting times of a job on two consecutive machines, there must enough time for the job to be processed on the first machine.…”

Section: Milp Models For Flowshop With Unlimited Buffermentioning

confidence: 99%

“…Preemptions are not allowed, that is, when a job starts to be processed on a machine, it cannot be interrupted. Among its several applications, one of the most relevant applications of flowshop can be found in the chemical industry [3,13]. Since specific equipment for chemical processes is expensive, there is a strong motivation to optimize this production environment.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Mixed-Integer Programming Models for Flowshop Scheduling Problems Minimizing the Total Earliness and Tardiness

Ronconi

Birgin

2011

Just-in-Time Systems

View full text Add to dashboard Cite

Scheduling problems involving both earliness and tardiness costs have received significant attention in recent years. This type of problem became important with the advent of the justin-time (JIT) concept, where early or tardy deliveries are highly discouraged. In this work we examine the flowshop scheduling problem with no storage constraints and with blocking inprocess. In this latter environment, there are no buffers between successive machines; therefore intermediate queues of jobs waiting in the system for their next operations are not allowed. Performance is measured by the minimization of the sum of earliness and tardiness of the jobs. Mixed-integer models that represent these scheduling flowshop problems are presented. The models are evaluated and compared in several problems using commercial known software.

show abstract

Section: Milp Models For Flowshop With Unlimited Buffermentioning

confidence: 99%

Section: Milp Models For Flowshop With Unlimited Buffermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Mixed-Integer Programming Models for Flowshop Scheduling Problems Minimizing the Total Earliness and Tardiness

Ronconi

Birgin

2011

Just-in-Time Systems

View full text Add to dashboard Cite

show abstract

“…Conseqüentemente, o número de variáveis/restrições do modelo tende a aumentar com a diminuição do valor do subintervalo. Se os dados do problema são arredondados, o valor do subintervalo pode aumentar, mas a solução obtida pode ser muito conservativa ou infactível (Reklaitis, 1992). Em uma abordagem temporal contínua, a ocorrência de eventos reais do sistema modelado é que determina a subdivisão temporal.…”

Section: Modelagem Do Problemaunclassified

“…Esta abordagem torna viável a obtenção de soluções operacionais para cenários reais do problema em tempo computacional adequado, no caso, poucos segundos. Esta subdivisão será baseada nos três elementos chave do scheduling: a determinação e a alocação dos recursos a serem utilizados (assignment), o seqüenciamento de atividades (sequencing) e a temporização (timing) do uso dos recursos pelas atividades (Reklaitis, 1992).…”

Section: Modelagem Do Problemaunclassified

Um modelo híbrido (CLP-MILP) para scheduling de operações em polidutos

2008

View full text Add to dashboard Cite

ResumoA eficácia na transferência de derivados de petróleo através de dutos motiva a execução deste trabalho. O objetivo principal é a modelagem do scheduling de um poliduto, isto é, um sistema de dutos que transporta diferentes derivados de petróleo. O poliduto em estudo com 93,5 km de extensão conecta uma refinaria a um terminal portuário. Foi desenvolvido um modelo de otimização baseado na união de Constraint Logic Programming (CLP) e Mixed Integer Linear Programming (MILP). O modelo utiliza uma abordagem de decomposição do problema, com representação temporal contínua e calcula janelas de tempo (restrições temporais) que devem ser respeitadas. A abordagem híbrida CLP-MILP proporcionou a solução de cenários reais em tempo computacional da ordem de segundos. A resolução computacional do modelo proposto evidenciou novos pontos de operação para o poliduto, proporcionando ganhos operacionais significativos. O modelo implementado configura uma ferramenta de auxílio para tomada de decisões operacionais no cenário estudado.Palavras-chave: busca orientada por restrições (CLP); programação linear inteira mista (MILP); programação operacional de polidutos. AbstractThis work is motivated by the need of optimization in the pipeline-oil distribution scenario. The considered problem involves the short-term scheduling of activities in a specific pipeline. The pipeline is 93.5 km in length, and it connects refinery and harbor tankfarms, conveying different types of commodities (gasoline, diesel, kerosene, etc). An optimization model was developed to determine the pipeline scheduling with improved efficiency. Such model combines Constraint Logic Programming (CLP) and Mixed Integer Linear Programming (MILP) in an integrated CLP-MILP framework. The proposed model uses decomposition strategies, continuous time representation, and intervals that represent time constraints (time windows). Real cases were solved in a reduced computational time (order of seconds). The computational results have demonstrated that the model is able to define new operational points to the pipeline, providing significant cost saving. Indeed the CLP-MILP model is an efficient tool to aid the operational decision-making within this real-world pipeline scenario.

show abstract