Hybrid modeling and simulation for complementing Lifecycle Assessment

Wang, Bochao; Brême, Séverin; Moon, Young B.

doi:10.1016/j.cie.2013.12.016

Cited by 45 publications

(23 citation statements)

References 15 publications

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“…Compared to other economic sectors, combined DEA-LCA studies in agri-food are few (see [95] for an example). Further improvements may arise from the use of system dynamics modelling to correct model estimates, e.g., with respect to temporal effects, rebound effects, and uncertainty [96]. Compared to economic aspects, LCA combination with social impact assessments has received less attention by researchers, though being key to allow consumer acceptability of innovative food production and consumption systems [69].…”

Section: Inclusion Of Economic and Social Aspectsmentioning

confidence: 99%

A Reflection of the Use of the Life Cycle Assessment Tool for Agri-Food Sustainability

et al. 2018

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In pursuit of agricultural sustainability and food security, research should contribute to policy-making by providing scientifically robust evidence. Life cycle assessment (LCA) is an excellent candidate for generating that evidence, thereby helping the selection of interventions towards more sustainable agri-food. The purpose of this article is proposing a basis for discussion on the use of the LCA tool for targeting and monitoring of environmental policy interventions in agri-food. The problem of reducing the environmental burden in agri-food can be tackled by acting on the supply and/or demand sides and may benefit from the collaboration of supply chain stakeholders. Agri-food policies that most benefit from LCA-based data concern cross-border pollution, transaction costs following the adoption of environmental standards, adoption of less polluting practices and/or technologies, and business-to-consumer information asymmetry. The choice between the methodological options available for LCA studies (attributional, consequential, or hybrid models) depends on the purpose and scope of the study. The possibility of integrating the LCA with economic and social impact assessments—e.g., under the life cycle sustainability assessment framework—makes LCA an excellent tool for monitoring business or sectoral-level achievements with respect to UN 2030 Sustainable Development Goals.

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Section: Inclusion Of Economic and Social Aspectsmentioning

confidence: 99%

A Reflection of the Use of the Life Cycle Assessment Tool for Agri-Food Sustainability

et al. 2018

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“…For example, a large-scale simulation model was developed to compare single-stream and dual-stream solid waste management alternatives in the state of Florida, US [43]. Another example is the model of [44], in which they show how to couple ABMS with other modeling methods in the context of life-cycle assessments.…”

Section: Simulation Of Waste Management Operationsmentioning

confidence: 99%

Agent-Based Model for End-of-Life Product Flow Analysis

Labelle

Frayret

2018

Resources

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This paper presents an agent-based simulation model for end-of-life product flow analysis in recuperation and recycling supply networks that focuses on individual consumer behaviors. The simulation model is applied to a deposit-return program on wine bottles that could be developed in the province of Quebec. Canadian data was used to calibrate and validate the model. A series of experiments was then conducted with three artificial populations to analyse how they would react to several implementation scenarios of this end-of-life product flow strategy. The results suggest that the distance to the nearest depot is an important decision factor, but less predominant than the ownership of a private vehicle and the deposit value. The results also indicate that the use of agent-based modeling combined with the theory of planned behavior (TPB) can produce modular behavior models, that are intuitive and simple, to better understand consumer-behavior-driven supply chains. Such models can be used to give insights to decision-makers and policy-makers about the potential performance of end-of-life product flows strategies and further facilitate efficient resource management.

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“…The work of Wang et al [20] has the authors conducting an analysis of the complementary cycle of life by utilizing the hybrid simulation to present a new complementary life cycle assessment (LCA) approach to address several limitations of the standard LCA methodology. The authors combined the three paradigms of a simulation -DES, SD, and ABMS -to simulate scenarios with the intention of decreasing the consumption of energy and pollution.…”

Section: Related Researchesmentioning

confidence: 99%

Dynamic Allocation of Additional Human Resources Using Hybrid Simulation

Sena¹,

Silva²,

Costa³

et al. 2017

Int. j. simul. model.

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This work simulated several alternatives for the dynamic allocation of additional human resources in a company that produces a group of specific products. The goal was to increase the average amount of the margin of the total contribution through a hybrid application of a discrete event simulation (DES) and an agent-based modelling simulation (ABMS). Two different decision-making forms were proposed to determine which workstation should receive an additional operator. The first proposal was based on the occupancy level of the operators, while the second one was based on the intermediate queue size. The computational model was operationally validated by comparing the results with actual production data from the company. Twelve scenarios were analysed using a margin of the established contribution. Based on the occupancy rate, the ratio improved on average by 27.68 %, with an additional operator in the workstation. According to the second criterion, this improvement raised to 117.51 %.

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Hybrid modeling and simulation for complementing Lifecycle Assessment

Cited by 45 publications

References 15 publications

A Reflection of the Use of the Life Cycle Assessment Tool for Agri-Food Sustainability

A Reflection of the Use of the Life Cycle Assessment Tool for Agri-Food Sustainability

Agent-Based Model for End-of-Life Product Flow Analysis

Dynamic Allocation of Additional Human Resources Using Hybrid Simulation

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