Combining mixed integer programming and constraint programming to solve the integrated scheduling problem of container handling operations of a single vessel

2020 ◽  
Vol 285 (3) ◽  
pp. 884-901 ◽  
Author(s):  
Tianbao Qin ◽  
Yuquan Du ◽  
Jiang Hang Chen ◽  
Mei Sha
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Constraint Programming ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Integrated Scheduling ◽  
Single Vessel ◽  
Container Handling

scholarly journals O uso do Mixed-Integer e Constraint Programming para a resolução do Job Shop Scheduling Problem

2019 ◽  
pp. 27-35
Author(s):  
Alvaro Neuenfeldt Júnior
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Constraint Programming ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Digital Or

Independente do processo industrial, o estudo sobre a alocação de recursos produtivos é atualmente um dos temas mais abordados cientificamente, principalmente quando envolve a busca pela gestão de forma mais eficiente e dinâmica às exigências do mercado ao qual a empresa está inserida. Para tanto, o presente artigo tem por objetivo comparar o desempenho de três técnicas de otimização ao contexto do Job Shop Scheduling Problem (JSSP), sendo uma baseada em modelagens Mixed-Integer Programming (MIP) e outras duas resolvidas com base nos conceitos do Constraint Programming (CP), por meio da utilização de 82 instâncias disponibilizadas pela biblioteca digital OR Library. Como resultados, foi possível verificar que a versão padrão do CP disponibilizado pelo software CPLEX Optimization Studio é o mais eficiente para encontrar soluções ótimas, conforme benchmark realizado com estudos anteriormente publicados cientificamente.

Mixed-integer Programming of Stochastic Hydro Self-scheduling Problem in Joint Energy and Reserves Markets

2016 ◽  
Vol 44 (7) ◽  
pp. 752-762 ◽  
Author(s):  
Mahmoud Sharafi Masouleh ◽  
Farshid Salehi ◽  
Fatima Raeisi ◽  
Mojtaba Saleh ◽  
Azade Brahman ◽  
...  
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Mixed Integer ◽  
Scheduling Problem

scholarly journals A Heuristic Approach for Determining Lot Sizes and Schedules Using Power-of-Two Policy

2007 ◽  
Vol 2007 ◽  
pp. 1-18
Author(s):  
Esra Ekinci ◽  
Arslan M. Ornek
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Flow Shop ◽  
Lot Sizing ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Binary Integer Programming ◽  
Multistage Manufacturing ◽  
Lot Sizing Problem ◽  
Lot Sizes

We consider the problem of determining realistic and easy-to-schedule lot sizes in a multiproduct, multistage manufacturing environment. We concentrate on a specific type of production, namely, flow shop type production. The model developed consists of two parts, lot sizing problem and scheduling problem. In lot sizing problem, we employ binary integer programming and determine reorder intervals for each product using power-of-two policy. In the second part, using the results obtained of the lot sizing problem, we employ mixed integer programming to determine schedules for a multiproduct, multistage case with multiple machines in each stage. Finally, we provide a numerical example and compare the results with similar methods found in practice.

scholarly journals Comparing Mixed-Integer Programming and Constraint Programming Models for the Hybrid Flow Shop Scheduling Problem with Dedicated Machines

2021 ◽  
Vol 54 (4) ◽  
pp. 591-597
Author(s):  
Asma Ouled Bedhief
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Constraint Programming ◽  
Flow Shop ◽  
Programming Model ◽  
Flow Shop Scheduling ◽  
Mixed Integer ◽  
Hybrid Flow Shop ◽  
Dedicated Machines ◽  
Hybrid Flow Shop Scheduling

The paper considers a two-stage hybrid flow shop scheduling problem with dedicated machines and release dates. Each job must be first processed on the single machine of stage 1, and then, the job is processed on one of the two dedicated machines of stage 2, depending on its type. Moreover, the jobs are available for processing at their respective release dates. Our goal is to obtain a schedule that minimizes the makespan. This problem is strongly NP-hard. In this paper, two mathematical models are developed for the problem: a mixed-integer programming model and a constraint programming model. The performance of these two models is compared on different problem configurations. And the results show that the constraint programming outperforms the mixed-integer programming in finding optimal solutions for large problem sizes (450 jobs) with very reasonable computing times.

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