Accelerating the Search for Optimal Solution of Integrated Process-Network Synthesis and Scheduling

Scheduling is crucial for effective implementations of production, manufacturing, and logistics. With rare exceptions of extremely simple cases, only mathematical programming, e.g., Mixed Integer Linear Programming (MILP), can guarantee the optimal answer to practical scheduling problems. Unfortunat...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Laszlo Szili, Marton Frits, Botond Bertok
Formato:	article
Lenguaje:	EN
Publicado:	AIDIC Servizi S.r.l. 2021
Materias:	Chemical engineering TP155-156 Computer engineering. Computer hardware TK7885-7895
Acceso en línea:	https://doaj.org/article/7301396b9ab341989a527a8e3c735845
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:7301396b9ab341989a527a8e3c735845
record_format	dspace
spelling	oai:doaj.org-article:7301396b9ab341989a527a8e3c7358452021-11-15T21:47:00ZAccelerating the Search for Optimal Solution of Integrated Process-Network Synthesis and Scheduling10.3303/CET21881982283-9216https://doaj.org/article/7301396b9ab341989a527a8e3c7358452021-11-01T00:00:00Zhttps://www.cetjournal.it/index.php/cet/article/view/11991https://doaj.org/toc/2283-9216Scheduling is crucial for effective implementations of production, manufacturing, and logistics. With rare exceptions of extremely simple cases, only mathematical programming, e.g., Mixed Integer Linear Programming (MILP), can guarantee the optimal answer to practical scheduling problems. Unfortunately, the applicability of general-purpose MILP solvers is limited by the required computational time. To achieve a sufficiently fast answer in practice by mathematical programming, a highly flexible solution procedure is needed that can be tailored to the problem under investigation. Solution methods utilizing graph theory in parallel with algebraic operations give more room for customization. Process Network Synthesis (PNS) and the P-graph framework were originally developed to design and optimize chemical engineering process structures with continuous operation. Time Constrained Process Network Synthesis (TCPNS) has made it capable to handle batch processes with time constraints and storage strategies. P-graph algorithms extended to TCPNS can solve the precedence-based MILP model formulation of scheduling problems and are highly customizable as well. The aim of the current research is to examine and find the most suitable decision variable selection strategy for P-graph framework’s optimization method to gain possible accelerations for different classes of scheduling problems.Laszlo SziliMarton FritsBotond BertokAIDIC Servizi S.r.l.articleChemical engineeringTP155-156Computer engineering. Computer hardwareTK7885-7895ENChemical Engineering Transactions, Vol 88 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Chemical engineering TP155-156 Computer engineering. Computer hardware TK7885-7895
spellingShingle	Chemical engineering TP155-156 Computer engineering. Computer hardware TK7885-7895 Laszlo Szili Marton Frits Botond Bertok Accelerating the Search for Optimal Solution of Integrated Process-Network Synthesis and Scheduling
description	Scheduling is crucial for effective implementations of production, manufacturing, and logistics. With rare exceptions of extremely simple cases, only mathematical programming, e.g., Mixed Integer Linear Programming (MILP), can guarantee the optimal answer to practical scheduling problems. Unfortunately, the applicability of general-purpose MILP solvers is limited by the required computational time. To achieve a sufficiently fast answer in practice by mathematical programming, a highly flexible solution procedure is needed that can be tailored to the problem under investigation. Solution methods utilizing graph theory in parallel with algebraic operations give more room for customization. Process Network Synthesis (PNS) and the P-graph framework were originally developed to design and optimize chemical engineering process structures with continuous operation. Time Constrained Process Network Synthesis (TCPNS) has made it capable to handle batch processes with time constraints and storage strategies. P-graph algorithms extended to TCPNS can solve the precedence-based MILP model formulation of scheduling problems and are highly customizable as well. The aim of the current research is to examine and find the most suitable decision variable selection strategy for P-graph framework’s optimization method to gain possible accelerations for different classes of scheduling problems.
format	article
author	Laszlo Szili Marton Frits Botond Bertok
author_facet	Laszlo Szili Marton Frits Botond Bertok
author_sort	Laszlo Szili
title	Accelerating the Search for Optimal Solution of Integrated Process-Network Synthesis and Scheduling
title_short	Accelerating the Search for Optimal Solution of Integrated Process-Network Synthesis and Scheduling
title_full	Accelerating the Search for Optimal Solution of Integrated Process-Network Synthesis and Scheduling
title_fullStr	Accelerating the Search for Optimal Solution of Integrated Process-Network Synthesis and Scheduling
title_full_unstemmed	Accelerating the Search for Optimal Solution of Integrated Process-Network Synthesis and Scheduling
title_sort	accelerating the search for optimal solution of integrated process-network synthesis and scheduling
publisher	AIDIC Servizi S.r.l.
publishDate	2021
url	https://doaj.org/article/7301396b9ab341989a527a8e3c735845
work_keys_str_mv	AT laszloszili acceleratingthesearchforoptimalsolutionofintegratedprocessnetworksynthesisandscheduling AT martonfrits acceleratingthesearchforoptimalsolutionofintegratedprocessnetworksynthesisandscheduling AT botondbertok acceleratingthesearchforoptimalsolutionofintegratedprocessnetworksynthesisandscheduling
_version_	1718426850063024128

Accelerating the Search for Optimal Solution of Integrated Process-Network Synthesis and Scheduling

Ejemplares similares