Operations scheduling for waste minimization: A review

Hesran, Corentin Le; Ladier, Anne-Laure; Botta‐Genoulaz, Valérie; Laforest, Valérie

doi:10.1016/j.jclepro.2018.09.136

Cited by 27 publications

(9 citation statements)

References 111 publications

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“…In addition, references cited in the selected papers or citing these papers were also considered for the exhaustive literature review discussed in Section 3 (Potential Applications). The content analysis approach provides an adequate number of results for a systematic review, and it has been used in other review papers [52][53][54]. It should be highlighted that the literature survey used for the subsequent sections accounts for all porous geopolymer foams, regardless of the foaming method (e.g.…”

Section: Methods For Identifying Relevant Literaturementioning

confidence: 99%

Geopolymer foams: An overview of recent advancements

Novais

Pullar

Labrincha

2020

Progress in Materials Science

214

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Section: Methods For Identifying Relevant Literaturementioning

confidence: 99%

Geopolymer foams: An overview of recent advancements

Novais

Pullar

Labrincha

2020

Progress in Materials Science

214

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“…In other words, the papers considering sustainability objectives other than energy efficiency are outside the scope of this work. (For a detailed breakdown of the various research clusters regarding sustainable manufacturing, the reader is referred to [5,43]). Also out of the scope of this review are works tackling higher levels of decision making (mid-and long-term), such as logistics, supply chain management, and business management, even if focusing on energy efficiency.…”

Section: Review Scope and Methodologymentioning

confidence: 99%

“…The increasing number of publications concerned with sustainable manufacturing has led to the publication of several reviews. As described in [3], early reviews focus on concepts and technologies, and more recent ones address (i) specific aspects of energy-aware production planning, such as power load scheduling [40], electric storage systems [41], smart grid [42], and waste minimization [43]; (ii) specific approaches, such as approaches in multi-objective environments [44], simulation [45], and machine learning [46]; (iii) sustainable practices [43,47,48]; or (iv) general manufacturing systems [3][4][5][6]44].…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Scheduling in Job Shop Manufacturing Systems: A Literature Review

2022

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Energy efficiency has become a major concern for manufacturing companies not only due to environmental concerns and stringent regulations, but also due to large and incremental energy costs. Energy-efficient scheduling can be effective at improving energy efficiency and thus reducing energy consumption and associated costs, as well as pollutant emissions. This work reviews recent literature on energy-efficient scheduling in job shop manufacturing systems, with a particular focus on metaheuristics. We review 172 papers published between 2013 and 2022, by analyzing the shop floor type, the energy efficiency strategy, the objective function(s), the newly added problem feature(s), and the solution approach(es). We also report on the existing data sets and make them available to the research community. The paper is concluded by pointing out potential directions for future research, namely developing integrated scheduling approaches for interconnected problems, fast metaheuristic methods to respond to dynamic scheduling problems, and hybrid metaheuristic and big data methods for cyber-physical production systems.

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“…This process is strongly interrelated and usually realized in parallel to the selection of the most appropriate technology (Step 3b). Multi-criteria mathematical modeling examines criteria that are usually in conflict in the decision-making process [31][32][33][34][35][36]. On this basis, and after screening all legislative constraints (e.g., environmental permits), the appropriate multi-criteria analysis technique needs to be determined.…”

Section: Optimal Selection Of the Sitementioning

confidence: 99%

Decision Support System to Implement Units of Alternative Biowaste Treatment for Producing Bioenergy and Boosting Local Bioeconomy

et al. 2020

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Lately, the model of circular economy has gained worldwide interest. Within its concept, waste is viewed as a beneficial resource that needs to be re-introduced in the supply chains, which also requires the use of raw materials, energy, and water to be minimized. Undeniably, a strong link exists between the bioeconomy, circular economy, bioproducts, and bioenergy. In this light, in order to promote a circular economy, a range of alternative options and technologies for biowaste exploitation are currently available. In this paper, we propose a generic methodological scheme for the development of small, medium, or large-scale units of alternative biowaste treatment, with an emphasis on the production of bioenergy and other bioproducts. With the use of multi-criteria decision analysis, the model simultaneously considers environmental, economic, and social criteria to support robust decision-making. In order to validate the methodology, the latter was demonstrated in a real-world case study for the development of a facility in the region of Serres, Greece. Based on the proposed methodological scheme, the optimal location of the facility was selected, based on its excellent assessment in criteria related to environmental performance, financial considerations, and local acceptance. Moreover, anaerobic digestion of agricultural residues, together with farming and livestock wastes, was recommended in order to produce bioenergy and bioproducts.

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Operations scheduling for waste minimization: A review

Cited by 27 publications

References 111 publications

Geopolymer foams: An overview of recent advancements

Geopolymer foams: An overview of recent advancements

Energy-Efficient Scheduling in Job Shop Manufacturing Systems: A Literature Review

Decision Support System to Implement Units of Alternative Biowaste Treatment for Producing Bioenergy and Boosting Local Bioeconomy

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