The use of an optimisation model to design a green supply chain

Chanchaichujit, Janya; Saavedra-Rosas, Jose; Quaddus, Mohammed; West, Martin

doi:10.1108/ijlm-10-2013-0121

Cited by 15 publications

(13 citation statements)

References 40 publications

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“…This study builds on the work of Chanchaichujit et al (2016) in which the authors developed a singleobjective optimization model for minimizing costs and GHG emissions for the Thai rubber supply chain. The multi-objective optimization model developed in this study includes objective function 1 for cost minimization, objective function 2 for GHG emission minimization and constraints 3-16 for the model constraints (See Tables A1 and B1 in the appendix).…”

Section: Research Methodology and Mathematical Formulationmentioning

confidence: 99%

“…Single objective linear programming models have one objective function requiring optimization. For example, Chanchaichujit et al (2016) used the single objective linear programming model to find the association between the quantity of rubber product flow between supply chain entities and the transportation mode and route, to minimize total GHG emissions. The authors considered GHG emissions and costs as two single objective functions and found the relationship between GHG emissions and costs to be in conflict with each other.…”

Section: Mathematical Modelling Based Approaches In Gscmmentioning

confidence: 99%

“…To date, very few studies on the rubber industry and even fewer on the Thai rubber supply chain have dealt with environmental and economic issues together. The few studies that were conducted (e.g., Chanchaichujit et al, 2016) only attempted a single-objective optimization. Here we have tried to generate a full set of trade-off solutions for both costs and GHG emissions so that (from a set of alternative solutions) the decision-maker can select the most appropriate (from their perspective) supply chain network design.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multi-objective decision model for green supply chain management

Chanchaichujit

Balasubramanian

Shukla

et al. 2020

Cogent Business & Management

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In this paper, a multi-objective linear programming model was developed which sought to simultaneously optimize total costs and total GHG emissions for the Thai Rubber supply chain. The model was solved by the ε -constraint method which computed the Pareto optimal solution. Each point in the Pareto set entailed a different design of quantity of rubber product flow between the supply chain entities and transport modes and routes. The result obtained show the trade-offs between costs and GHG emissions. It appears that improvements in cost reductions are only possible by compromising on and allowing for higher GHG emissions. From the Pareto set of solutions, each point is equally effective solution for achieving significant cost reductions without compromising too far on GHG emissions. Scenarios analysis were considered to examine the impact of transportation and distribution restructuring on the trade-off between GHG emissions and costs vis-àvis the baseline model. Overall, the model developed in this research, together with its Pareto optimal solutions analysis, shows that it can be used as an effective tool to design a new and workable GSCM model for the Thai Rubber industry. ABOUT THE AUTHORSJanya Chanchaichujit is an Assistant Professor in Logistics Management in the School of Management at Walailak University in Thailand. Dr. Chanchaichujit has over twenty years industrial, project consultancy and academic work experience. Her research interest focuses on incorporating various aspects of operational research applications, and technologies into the design and operation of sustainable supply chain management.

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Section: Research Methodology and Mathematical Formulationmentioning

confidence: 99%

Section: Mathematical Modelling Based Approaches In Gscmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Multi-objective decision model for green supply chain management

Chanchaichujit

Balasubramanian

Shukla

et al. 2020

Cogent Business & Management

Self Cite

View full text Add to dashboard Cite

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“…Similar practices were carried out in Shim and Kumar (2010) and Islam (2018). Additionally, in accordance with Chanchaichujit et al (2016)'s suggestion that model validity and reliability may be conducted by a group of industry experts, the baseline model's simulated results were evaluated by related port operators. It can be concluded that the simulated results are certainly capable of providing realistic results.…”

Section: Model Validationmentioning

confidence: 99%

Impact of service policies on terminal gate efficiency: a simulation approach

Chamchang

Niyomdecha

2021

Cogent Business & Management

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Congestion at terminal gates is a significant issue that many ports are dealing with. The port of Songkhla, which serves as the main seaport in southern Thailand, has been confronted with this issue, together with an increase in the number of trucks over the last five years. This study aims to investigate alternatives for improving service operations at the terminal gate, including gate lane expansion, queueing policy in exit-gate sharing, and work process reorganization. A simulation model was developed to analyze the queueing performance: truck queue length and gate waiting time. Scenarios analysis was performed and compared to the baseline model to investigate the impact of proposed approaches on gate performance. The simulation results confirm that a gate-sharing policy can alleviate congestion at a certain truck arrival rate. The method of reorganizing work processes by separating customs work from gate operations and placing it in a new work station appears most appealing. It produces a significant improvement in congestion, comparable to the performance of the gate lane expansion approach while requiring less investment.

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“…In this sense, several initiatives aimed at reducing the impact of logistics activities such as switching to use more environmentally friendly transport modes, consolidation of goods, and running an eco-efficient fleet can be implemented (Tacken et al , 2014). Thus, the fundamental shift is to properly integrate the environmental issues in planning the business strategies (Chanchaichujit et al , 2016). For example, the UK policy is aimed at stimulating the diffusion of low-impact vehicles based on fiscal incentives for hybrid and electric tractions (Brand et al , 2013).…”

Section: Literature Reviewmentioning

confidence: 99%

Analyzing the diffusion of eco-friendly vans for urban freight distribution

Cagliano

Carlin

Mangano

et al. 2017

IJLM

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Purpose The purpose of this paper is to investigate the diffusion dynamics of electric and hybrid commercial vans and its enabling factors in the city logistics (CL) contexts. The case of parcel delivery in Torino, Italy, is considered. Attention is paid to the influence on the choice of low impact vehicles of not only public strategies but also operational aspects characterizing urban freight distribution systems. Design/methodology/approach A System Dynamics model based on the Bass diffusion theory computes the number of adopters of low-emission vehicles together with the quantity of vans required and the associated economic savings. The model includes variables about freight demand, delivery frequency, van carrying capacity, routes, stops, distances traveled, and vehicle charging stations. A sensitivity analysis has been completed to identify the main diffusion levers. The focus is on advertising and other drivers, such as public contributions, taxes traditional polluting vehicles are subjected to, as well as on routing optimization strategies. Findings Advertising programs, green image, and word-of-mouth drive market saturation, although in a long time period. In fact, low-impact vehicles do not offer any economic advantage over traditional ones requiring higher investment and operating costs. Public incentives to purchase both green vehicles and charging stations, together with carbon taxes and a congestion charge affecting polluting vehicles, are able to shorten the adoption time. In particular, public intervention reveals to be effective only when it unfolds through a number of measures that both facilitate the use of environmentally friendly vehicles and discourage the adoption of traditional commercial vans. Route optimization also hastens the complete market saturation. Research limitations/implications This work fosters research about the mutual relationships between the diffusion of low-emission commercial vehicles and the operational and contextual CL factors. It provides a structured approach for investigating the feasibility of innovative good vehicles that might be part of assessments of CL measures and requirements. Finally, the model supports studies about the cooperation among stakeholders to identify effective commercial vehicle fleets. Practical implications This study fosters collaboration among CL players by providing a roadmap to identify the key factors for the diffusion of environmentally friendly freight vehicles. It also enables freight carriers to assess the operational and economic feasibility of adopting low-impact vehicles. Finally, it might assist public authorities in capturing the effects of new urban transportation policies prior to their implementation. Originality/value Most of the current CL literature defines policies and analyzes their effects. Also, there are several contributions on the diffusion of low emission cars. The present study is one of the first works on the diffusion of low-impact commercial vehicles in urban areas by considering the associated key operational factors. A further value is that the proposed model combines operational variables with economic and environmental issues.

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The use of an optimisation model to design a green supply chain

Cited by 15 publications

References 40 publications

Multi-objective decision model for green supply chain management

Multi-objective decision model for green supply chain management

Impact of service policies on terminal gate efficiency: a simulation approach

Analyzing the diffusion of eco-friendly vans for urban freight distribution

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