Sustainable scheduling of batch processes under economic and environmental criteria with MINLP models and algorithms

•Sustainable scheduling for multiproduct and multipurpose batch plants is investigated.•Multi-objective optimization model under economic and environmental criteria is proposed.•Maximizing productivity as the economic objective.•Minimizing environmental impact per functional unit as the environmenta...

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Bibliographic Details
Published in:Computers & chemical engineering Vol. 54; pp. 44 - 59
Main Authors: Yue, Dajun, You, Fengqi
Format: Journal Article
Language:English
Published: Kidlington Elsevier Ltd 11.07.2013
Elsevier
Subjects:
Applied sciences
Batch manufacturing
Chemical engineering
Computer science; control theory; systems
Control theory. Systems
Exact sciences and technology
Global optimization
LCA
Mechanical engineering. Machine design
Metrology, automation
Multiobjective optimization
Operational research and scientific management
Operational research. Management science
Process control. Computer integrated manufacturing
Process operations
Scheduling, sequencing
Sustainability
Batch manufacturing
Process operations
Global optimization
LCA
Sustainability
Multiobjective optimization
Short term
Chemical engineering
Makespan
Multiple production
Sustainable development
Modeling
Convex programming
Optimization
Life cycle
Linearization
Productivity
Pareto optimum
Global optimum
Mixed integer programming
Scheduling
Case study
Environment impact
Batch process
Non linear effect
Non convex analysis
ISSN:0098-1354, 1873-4375
Online Access:Get full text
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Summary:•Sustainable scheduling for multiproduct and multipurpose batch plants is investigated.•Multi-objective optimization model under economic and environmental criteria is proposed.•Maximizing productivity as the economic objective.•Minimizing environmental impact per functional unit as the environmental objective.•Tailored Dinkelbach's algorithm and reformulation-linearization method to optimize resulting MILFP problems effectively. We address the bi-criterion optimization of batch scheduling problems with economic and environmental concerns. The economic objective is expressed in terms of productivity, which is the profit rate with respect to the makespan. The environmental objective is evaluated by means of environmental impact per functional unit based on the life cycle assessment methodology. The bi-criterion optimization model is solved with the ε-constraint method. Each instance is formulated as a mixed-integer linear fractional program (MILFP), which is a special class of non-convex mixed-integer nonlinear programs. In order to globally optimize the resulting MILFPs effectively, we employ the tailored reformulation-linearization method and Dinkelbach's algorithm. The optimal solutions lead to a Pareto frontier that reveals the tradeoff between productivity and environmental impact per functional unit. To illustrate the application, we present two case studies on the short-term scheduling of multiproduct and multipurpose batch plants.
ISSN:0098-1354
1873-4375
DOI:10.1016/j.compchemeng.2013.03.013