Scheduling Theory and Algorithms for Sustainable Manufacturing

This reprint of a Special Issue of Algorithms presents recent research on the applications of planning and scheduling models and algorithms to production systems and logistics, with the objective to increase production systems' sustainability. In the eleven research papers, several advanced models a...

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collection Directory of Open Access Books
description This reprint of a Special Issue of Algorithms presents recent research on the applications of planning and scheduling models and algorithms to production systems and logistics, with the objective to increase production systems' sustainability. In the eleven research papers, several advanced models and algorithms for different sustainability issues are proposed to optimize energy consumption and achieve environmental benefits and resilience, as well as demonstrate how to reduce the cost of installing photovoltaic systems, organize sustainable inventory management, etc.
format Online
id doab-20.500.12854ir-165110
institution Directory of Open Access Books
language eng
publishDate 2025
publishDateRange 2025
publishDateSort 2025
publisher MDPI - Multidisciplinary Digital Publishing Institute
publisherStr MDPI - Multidisciplinary Digital Publishing Institute
record_format ojs
spelling doab-20.500.12854ir-1651102025-08-12T08:02:34Z Scheduling Theory and Algorithms for Sustainable Manufacturing Dolgui, Alexandre Lemoine, David Restrepo, María I. Werner, Frank product-driven nervousness schedule planning intelligent product agent-based model holonic manufacturing system slime mold algorithm fair scheduling Bernoulli mapping reverse learning Cauchy mutation heuristics scheduling algorithms constraint satisfaction problems resource allocation co-activity conflict mitigation many-objective optimization ideal stock optimization sustainable supply chain stock management cost-effective logistics photovoltaic sets multi-criteria decision making micro solar generation generation optimisation sustainable scheduling fleet of drones maximizing the environmental benefit polynomial-time algorithm bibliometric analysis production scheduling reinforcement learning parallel machine scheduling problem ore hauling equipment mathematical model mining industry disruption handling machine breakage part input sequencing FMS scheduling dynamic scheduling reactive scheduling flexible job shop scheduling energy savings make-span two-level MILP remanufacturing circular economy machine learning data-driven models sustainability n/a thema EDItEUR::K Economics, Finance, Business and Management::KC Economics This reprint of a Special Issue of Algorithms presents recent research on the applications of planning and scheduling models and algorithms to production systems and logistics, with the objective to increase production systems' sustainability. In the eleven research papers, several advanced models and algorithms for different sustainability issues are proposed to optimize energy consumption and achieve environmental benefits and resilience, as well as demonstrate how to reduce the cost of installing photovoltaic systems, organize sustainable inventory management, etc. 2025-08-12T08:02:32Z 2025-08-12T08:02:32Z 2025 book ONIX_20250812T095121_9783725831647_59 9783725831647 9783725831630 https://directory.doabooks.org/handle/20.500.12854/165110 eng image/jpeg Attribution 4.0 International https://mdpi.com/books https://mdpi.com/books/pdfview/book/10482 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-3163-0 10.3390/books978-3-7258-3163-0 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725831647 9783725831630 222 open access
spellingShingle product-driven
nervousness
schedule
planning
intelligent product
agent-based model
holonic manufacturing system
slime mold algorithm
fair scheduling
Bernoulli mapping
reverse learning
Cauchy mutation
heuristics
scheduling algorithms
constraint satisfaction problems
resource allocation
co-activity conflict mitigation
many-objective optimization
ideal stock optimization
sustainable supply chain
stock management
cost-effective logistics
photovoltaic sets
multi-criteria decision making
micro solar generation
generation optimisation
sustainable scheduling
fleet of drones
maximizing the environmental benefit
polynomial-time algorithm
bibliometric analysis
production scheduling
reinforcement learning
parallel machine scheduling problem
ore hauling equipment
mathematical model
mining industry
disruption handling
machine breakage
part input sequencing
FMS scheduling
dynamic scheduling
reactive scheduling
flexible job shop
scheduling
energy savings
make-span
two-level MILP
remanufacturing
circular economy
machine learning
data-driven models
sustainability
n/a
thema EDItEUR::K Economics, Finance, Business and Management::KC Economics
Scheduling Theory and Algorithms for Sustainable Manufacturing
title Scheduling Theory and Algorithms for Sustainable Manufacturing
title_full Scheduling Theory and Algorithms for Sustainable Manufacturing
title_fullStr Scheduling Theory and Algorithms for Sustainable Manufacturing
title_full_unstemmed Scheduling Theory and Algorithms for Sustainable Manufacturing
title_short Scheduling Theory and Algorithms for Sustainable Manufacturing
title_sort scheduling theory and algorithms for sustainable manufacturing
topic product-driven
nervousness
schedule
planning
intelligent product
agent-based model
holonic manufacturing system
slime mold algorithm
fair scheduling
Bernoulli mapping
reverse learning
Cauchy mutation
heuristics
scheduling algorithms
constraint satisfaction problems
resource allocation
co-activity conflict mitigation
many-objective optimization
ideal stock optimization
sustainable supply chain
stock management
cost-effective logistics
photovoltaic sets
multi-criteria decision making
micro solar generation
generation optimisation
sustainable scheduling
fleet of drones
maximizing the environmental benefit
polynomial-time algorithm
bibliometric analysis
production scheduling
reinforcement learning
parallel machine scheduling problem
ore hauling equipment
mathematical model
mining industry
disruption handling
machine breakage
part input sequencing
FMS scheduling
dynamic scheduling
reactive scheduling
flexible job shop
scheduling
energy savings
make-span
two-level MILP
remanufacturing
circular economy
machine learning
data-driven models
sustainability
n/a
thema EDItEUR::K Economics, Finance, Business and Management::KC Economics
topic_facet product-driven
nervousness
schedule
planning
intelligent product
agent-based model
holonic manufacturing system
slime mold algorithm
fair scheduling
Bernoulli mapping
reverse learning
Cauchy mutation
heuristics
scheduling algorithms
constraint satisfaction problems
resource allocation
co-activity conflict mitigation
many-objective optimization
ideal stock optimization
sustainable supply chain
stock management
cost-effective logistics
photovoltaic sets
multi-criteria decision making
micro solar generation
generation optimisation
sustainable scheduling
fleet of drones
maximizing the environmental benefit
polynomial-time algorithm
bibliometric analysis
production scheduling
reinforcement learning
parallel machine scheduling problem
ore hauling equipment
mathematical model
mining industry
disruption handling
machine breakage
part input sequencing
FMS scheduling
dynamic scheduling
reactive scheduling
flexible job shop
scheduling
energy savings
make-span
two-level MILP
remanufacturing
circular economy
machine learning
data-driven models
sustainability
n/a
thema EDItEUR::K Economics, Finance, Business and Management::KC Economics
url ONIX_20250812T095121_9783725831647_59