Detail publikace

Non-linear Programming via P-graph Framework

HOW, B., TENG, S., LEONG, W., NG, W., LIM, C., NGAN, S., LAM, H.

Originální název

Non-linear Programming via P-graph Framework

Typ

článek v časopise ve Scopus, Jsc

Jazyk

angličtina

Originální abstrakt

P-graph is a graph-theoretic method which is designed to solve process network synthesis (PNS) problem using combinatorial and optimisation algorithms. Due to its visual interface for data encoding and results display; and its capability of generating multiple solutions (optimal and sub-optimal) simultaneously, the utility of P-graph has expanded into a broad range of studies recently.However, this powerful graph-theoretic method still falls short of dealing with non-linear problems. The problem can be found from the cost estimation provided by P-graph software. Despite it allows users to input the sizing cost (noted as “proportional cost” in P-graph software), the capacity and the cost are assumed to be linearly correlated. This inaccurate and unreliable cost estimation has increased the difficulty of making optimal decisions and therefore lead to undesirable profit loss. This paper proposes to solve the fundamental linearity problem by implementing trained artificial neural networks (ANN) into P-graph. To achieve this, an ANN model which utilised thresholded rectified linear unit (ReLU) activation function is developed in a segregated computational tool. The identified neurons are then modelled in P-graph in order to convert the input into the nonlinear output. To demonstrate the effectiveness of the proposed method, an illustrative case study of biomass transportation is used. With the use of the trained neurons, the non-linear estimation of transportation cost which considered fuel consumption cost, vehicle maintenance cost and labour cost are successfully modelled in P-graph. This work is expected to pave ways for P-graph users to expand the utility of P-graph in solving other more complex non-linear problems.

Klíčová slova

Non-linear programming, P-graph, Artificial Neural Network, Optimization, Artificial Intelligence

Autoři

HOW, B., TENG, S., LEONG, W., NG, W., LIM, C., NGAN, S., LAM, H.

Vydáno

30. 10. 2019

Nakladatel

AIDIC Servizi S.r.l.

Místo

Milan, Italy

ISSN

2283-9216

Periodikum

Chemical Engineering Transactions

Ročník

76

Číslo

1

Stát

Italská republika

Strany od

499

Strany do

504

Strany počet

6

URL

https://www.aidic.it/cet/19/76/084.pdf

BibTex

@article{BUT160581,
  author="Sin Yong {Teng}",
  title="Non-linear Programming via P-graph Framework",
  journal="Chemical Engineering Transactions",
  year="2019",
  volume="76",
  number="1",
  pages="499--504",
  doi="10.3303/CET1976084",
  issn="2283-9216",
  url="https://www.aidic.it/cet/19/76/084.pdf"
}