Interval-parameter chance-constraint programming model for end-of-life vehicles management under rigorous environmental regulations

2016 ◽  
Vol 52 ◽  
pp. 180-192 ◽  
Author(s):  
Vladimir Simic
Keyword(s):  
End Of Life ◽  
Constraint Programming ◽  
Programming Model ◽  
Environmental Regulations ◽  
Chance Constraint ◽  
Interval Parameter ◽  
Chance Constraint Programming ◽  
Constraint Programming Model

scholarly journals Bi-level chance constraint programming model for hazardous materials distribution

Filomat ◽  
2018 ◽  
Vol 32 (5) ◽  
pp. 1747-1755
Author(s):  
Zhanzhong Wang ◽  
Liying Zhao ◽  
Ningbo Cao ◽  
Mingtao Chen
Keyword(s):  
Programming Model ◽  
Transportation Cost ◽  
Hazardous Materials ◽  
Distribution Patterns ◽  
Chance Constraint ◽  
Chance Measure ◽  
Chance Constraint Programming ◽  
Upper Level ◽  
Constraint Programming Model ◽  
Fuzzy Random

With the growing presence of hazardous materials in daily life, a large number of institutions and scholars have been paying close attention to this field, providing new directions for exploring hazardous materials distribution patterns. This paper employs two fuzzy random variables, transportation cost and risk, to put forward a bi-level minimum objective programming model with a chance measure constraint within a specified chance level. The lower level is to seek minimum transportation costs and the upper level is for minimum risk. The model presented in this article simultaneously designs the hybrid algorithm, which is the combination of the fuzzy random simulation with the genetic algorithm. In the end, a smallscale instance is given to account for the efficiency of the presented model and algorithm, and the best distribution solution is presented.

A multi-shop integrated scheduling algorithm with fixed output constraint

2021 ◽  
pp. 1-9
Author(s):  
Yingchun Xia ◽  
Zhiqiang Xie ◽  
Yu Xin ◽  
Xiaowei Zhang
Keyword(s):  
Constraint Programming ◽  
Programming Model ◽  
Scheduling Algorithm ◽  
Processing Parameters ◽  
Scheduling Problem ◽  
Integrated Scheduling ◽  
Scheduling Scheme ◽  
Wide Range ◽  
Constraint Programming Model ◽  
Output Constraint

The customized products such as electromechanical prototype products are a type of product with research and trial manufacturing characteristics. The BOM structures and processing parameters of the products vary greatly, making it difficult for a single shop to meet such a wide range of processing parameters. For the dynamic and fuzzy manufacturing characteristics of the products, not only the coordinated transport time of multiple shops but also the fact that the product has a designated output shop should be considered. In order to solve such Multi-shop Integrated Scheduling Problem with Fixed Output Constraint (MISP-FOC), a constraint programming model is developed to minimize the total tardiness, and then a Multi-shop Integrated Scheduling Algorithm (MISA) based on EGA (Enhanced Genetic Algorithm) and B&B (Branch and Bound) is proposed. MISA is a hybrid optimization method and consists of four parts. Firstly, to deal with the dynamic and fuzzy manufacturing characteristics, the dynamic production process is transformed into a series of time-continuous static scheduling problem according to the proposed dynamic rescheduling mechanism. Secondly, the pre-scheduling scheme is generated by the EGA at each event moment. Thirdly, the jobs in the pre-scheduling scheme are divided into three parts, namely, dispatched jobs, jobs to be dispatched, and jobs available for rescheduling, and at last, the B&B method is used to optimize the jobs available for rescheduling by utilizing the period when the dispatched jobs are in execution. Google OR-Tools is used to verify the proposed constraint programming model, and the experiment results show that the proposed algorithm is effective and feasible.

scholarly journals REGIONAL ENERGY SUPPLY PLANNING: CHANCE CONSTRAINT PROGRAMMING

2019 ◽  
Vol 9 (5) ◽  
pp. 433-441
Author(s):  
Alimorad Sharifi ◽  
Nasim Mansouri ◽  
Babak Saffari ◽  
Shahram Moeeni
Keyword(s):  
Constraint Programming ◽  
Energy Supply ◽  
Chance Constraint ◽  
Regional Energy ◽  
Chance Constraint Programming ◽  
Supply Planning

Robust Fuzzy chance constraint programming for multi-item EOQ model with random disruption and partial backordering under uncertainty

2019 ◽  
Vol 36 (5) ◽  
pp. 276-285 ◽  
Author(s):  
Soheyl Khalilpourazari ◽  
Shima Teimoori ◽  
Abolfazl Mirzazadeh ◽  
Seyed Hamid Reza Pasandideh ◽  
Nasim Ghanbar Tehrani
Keyword(s):  
Constraint Programming ◽  
Chance Constraint ◽  
Eoq Model ◽  
Partial Backordering ◽  
Chance Constraint Programming

scholarly journals A new constraint programming model and solving for the cyclic hoist scheduling problem

Constraints ◽  
2020 ◽  
Vol 25 (3-4) ◽  
pp. 319-337 ◽  
Author(s):  
Mark Wallace ◽  
Neil Yorke-Smith
Keyword(s):  
Constraint Programming ◽  
Programming Model ◽  
State Of The Art ◽  
Scale Up ◽  
Generic Model ◽  
Scheduling Problem ◽  
Hoist Scheduling ◽  
Wide Range ◽  
Constraint Programming Model ◽  
High Level

AbstractThe cyclic hoist scheduling problem (CHSP) is a well-studied optimisation problem due to its importance in industry. Despite the wide range of solving techniques applied to the CHSP and its variants, the models have remained complicated and inflexible, or have failed to scale up with larger problem instances. This article re-examines modelling of the CHSP and proposes a new simple, flexible constraint programming formulation. We compare current state-of-the-art solving technologies on this formulation, and show that modelling in a high-level constraint language, MiniZinc, leads to both a simple, generic model and to computational results that outperform the state of the art. We further demonstrate that combining integer programming and lazy clause generation, using the multiple cores of modern processors, has potential to improve over either solving approach alone.

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