2008
DOI: 10.1016/j.jclepro.2006.08.028
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Metaheuristic multiobjective optimisation approach for the scheduling of multiproduct batch chemical plants

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Cited by 22 publications
(7 citation statements)
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“…Using a mixed integer dynamic optimization model, they generate a three-dimensional Pareto frontier from which a schedule can be selected. Arbiza et al (2008) present an LCA-based optimization process, where financial and environmental modules that assess a schedule's economic and environ-mental impacts are proposed. By using different recipes and raw materials for a same product, the schedule can be adapted according to both modules.…”
Section: Process Requirementsmentioning
confidence: 99%
“…Using a mixed integer dynamic optimization model, they generate a three-dimensional Pareto frontier from which a schedule can be selected. Arbiza et al (2008) present an LCA-based optimization process, where financial and environmental modules that assess a schedule's economic and environ-mental impacts are proposed. By using different recipes and raw materials for a same product, the schedule can be adapted according to both modules.…”
Section: Process Requirementsmentioning
confidence: 99%
“…María José Arbiza, Anna Bonfill, Gonzalo Guillén, Fernando D. Mele, Antonio Espuña and Luis Puigjaner authored the paper titled, ''Metaheuristic multiobjective optimisation approach for the scheduling of multiproduct batch chemical plants'' [13]. They introduced a novel framework for dealing with the batch production plants' scheduling problems.…”
Section: Cleaner Batch Processesmentioning
confidence: 99%
“…This metaheuristic algorithm considers some elementary operations (selection, crossover, mutation) that are widely described in the literature (Konak et al, 2006). Several studies have used a GA as a multiobjective optimization solver in order to identify the operating input parameters of thermal or chemical processes (Yuzgec et al, 2006;Arbiza et al, 2008;Sendín et al, 2010;Liu and Sun, 2013). In addition, model predictive control (MPC) is a relatively recent technique for the optimal control of processes; by its simplicity, it has created a real interest in the industrial field (Morari and Leeb, 1999;Qin and Badgwellb, 2003).…”
Section: Introductionmentioning
confidence: 99%