Optimal processing network design under uncertainty for producing fuels and value-added bioproducts from microalgae: Two-stage adaptive robust mixed integer fractional programming model and computationally efficient solution algorithm

AIChE Journal ◽  
2016 ◽  
Vol 63 (2) ◽  
pp. 582-600 ◽  
Author(s):  
Jian Gong ◽  
Fengqi You
Keyword(s):  
Fractional Programming ◽  
Efficient Solution ◽  
Programming Model ◽  
Value Added ◽  
Solution Algorithm ◽  
Mixed Integer ◽  
Design Under Uncertainty ◽  
Computationally Efficient ◽  
Optimal Processing ◽  
Processing Network

scholarly journals Opportunities to Optimize the Palm Oil Supply Chain in Sumatra, Indonesia

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 420 ◽  
Author(s):  
Fumi Harahap ◽  
Sylvain Leduc ◽  
Sennai Mesfun ◽  
Dilip Khatiwada ◽  
Florian Kraxner ◽  
...  
Keyword(s):  
Supply Chain ◽  
Palm Oil ◽  
Programming Model ◽  
Value Added ◽  
System Optimization ◽  
Energy System ◽  
Mixed Integer ◽  
Small Scale ◽  
Full Potential ◽  
Oil Supply

Significant amounts of biomass residues were generated in Indonesia. While untreated, residues emit greenhouse gases during the decomposition process. On the other hand, if efficiently utilized, these residues could be used to produce value-added products. This study investigates opportunities for harnessing the full potential of palm oil residues (i.e., empty fruit bunches, kernel shells, fiber, and mill effluent). As far as we are aware, the study is the first attempt to model the palm oil supply chain in a geographically explicit way while considering regional infrastructures in Sumatra Island, Indonesia. The BeWhere model, a mixed integer linear programming model for energy system optimization, was used to assess the costs and benefits of optimizing the regional palm oil supply chain. Different scenarios were investigated, considering current policies and new practices leading to improved yields in small-scale plantations and power grid connectivity. The study shows that a more efficient palm oil supply chain can pave the way for the country to meet up to 50% of its national bioenergy targets by 2025, and emission reductions of up to 40 MtCO2eq/year. As much as 50% of the electricity demand in Sumatra could be met if residues are efficiently used and grid connections are available. We recommend that system improvements be done in stages. In the short to medium term, improving the smallholder plantation yield is the most optimal way to maximize regional economic gains from the palm oil industry. In the medium to long term, improving electricity grid connection to palm oil mills could bring higher economic value as excess electricity is commercialized.

scholarly journals Wave Planning for Cart Picking in a Randomized Storage Warehouse

2020 ◽  
Vol 10 (22) ◽  
pp. 8050
Author(s):  
Jiun-Yan Shiau ◽  
Jie-An Huang
Keyword(s):  
Best Practice ◽  
Time Window ◽  
Programming Model ◽  
Value Added ◽  
Order Picking ◽  
Mixed Integer ◽  
Just In Time ◽  
Distribution Centers ◽  
Truck Loading ◽  
Planning Algorithm

Randomized storage strategy is known as a best practice for storing books of an online bookstore, it simplifies the order picking strategy as to retrieve books in purchase orders from closest locations of the warehouse. However, to be more responsive to customers, many distribution centers have adopted a just-in-time strategy leading to various value-added activities such as kitting, labelling, product or order assembly, customized packaging, or palletization, all of which must be scheduled and integrated in the order-picking process, and this is known as wave planning. In this study, we present a wave planning mathematical model by simultaneously consider: (1) time window from master of schedule (MOS), (2) random storage stock-keeping units (SKUs), and (3) picker-to-order. A conceptual simulation, along with a simplified example for the proposed wave planning algorithm, has been examined to demonstrate the merits of the idea. The result shows the wave planning module can improve the waiting time for truck loading of packages significantly and can reduce the time that packages are heaping in buffer area. The main contribution of this research is to develop a mixed integer programming model that helps the bookseller to generate optimal wave picking lists for a given time window.

An Efficient Solution Algorithm for Large-Scale Stochastic Mixed-Integer Linear Programs1

2012 ◽  
Vol 45 (15) ◽  
pp. 892-897
Author(s):  
Arul Sundaramoorthy ◽  
Xiang Li ◽  
James M.B. Evans ◽  
Paul I. Barton
Keyword(s):  
Large Scale ◽  
Efficient Solution ◽  
Solution Algorithm ◽  
Mixed Integer

scholarly journals A Metaheuristic Method for the Task Assignment Problem in Continuous-Casting Production

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Hongtao Hu ◽  
Yiwei Wu ◽  
Tingsong Wang
Keyword(s):  
Continuous Casting ◽  
Molten Steel ◽  
Assignment Problem ◽  
Programming Model ◽  
Task Assignment ◽  
Solution Algorithm ◽  
Mixed Integer ◽  
Computational Time ◽  
Solution Quality ◽  
Task Assignment Problem

The steelmaking and continuous-casting (SCC) process in integrated iron and steel enterprises can be described as two stages: the upstream stage and downstream stage. Raw materials are transformed into molten steel in the upstream stage, while the downstream stage is responsible for transforming molten steel which is released at regular intervals and has a limited time for being turned into slabs. This article focuses on the task assignment problem in the downstream stage within the given information resulting from the upstream stage. This problem is formulated as a nonlinear mixed-integer programming model aimed at minimizing total tardiness within the resource constraints and time windows constraints for the tasks. An improved solution algorithm based on particle swam optimization is developed to efficiently solve the proposed model. Finally, computational experiments are implemented to evaluate the performance of the solution algorithm in terms of solution quality and computational time.

Analysis on the Penetration Level of Wind Farm Considering Transient Stability Constraint and Uncertainty of Wind Power

2020 ◽  
Vol 13 (7) ◽  
pp. 1078-1086
Author(s):  
Bai Hao ◽  
Huang Andi ◽  
Zhou Changcheng
Keyword(s):  
Wind Power ◽  
Energy Function ◽  
Wind Farm ◽  
Transient Stability ◽  
Programming Model ◽  
Forecast Error ◽  
Credibility Theory ◽  
Mixed Integer ◽  
Stability Constraint ◽  
Level Problem

Background: The penetration level of a wind farm with transient stability constraint and static security constraint has been a key problem in wind power applications. Objective: The study explores maximum penetration level problem of wind considering transient stability constraint and uncertainty of wind power out, based on credibility theory and corrected energy function method. Methods: According to the corrected energy function, the transient stability constraint of the power grid is transferred to the penetration level problem of a wind farm. Wind speed forecast error is handled as a fuzzy variable to express the uncertainty of wind farm output. Then this paper builds a fuzzy chance-constrained model to calculate wind farm penetration level. To avoid inefficient fuzzy simulation, the model is simplified to a mixed integer linear programming model. Results: The results validate the proposed model and investigate the influence of grid-connection node, wind turbine characteristic, fuzzy reliability index, and transient stability index on wind farm penetration level. Conclusion: The result shows that the model proposed in this study can consider the uncertainty of wind power out and establish a quantitative transient stability constraint to determine the wind farm penetration level with a certain fuzzy confidence level.

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