Investigating carbon emissions in a production-inventory model under imperfect production, inspection errors and service-level constraint

Production-Distribution Model Considering Traceability and Carbon Emission: A Case Study of the Indonesian Canned Fish Food Industry

“…The same result was conveyed by Phatak [68] in his research which states that carbon emissions occur in various stages of food processing that involve machines in the production system [69]. In addition, according to Aktas and Temis [20] and Saga, Jauhari, Laksono, and Dwicahyani [70], the increase in the number of products causes a significantly greater amount of production, which can trigger large carbon emissions. This statement is supported by the facts shown in Tables 7 and 10.…”

“…Likewise, Moon et al [24] included the demand parameters and carbon emission limits in the bi-objective optimization problem model with mixed-integer linear programming. These two parameters have been used for the development of mathematical models by other researchers such as Saga et al [70], Manupati et al [23], Jauhari [71], and Mishra et al [52]. Meanwhile, Sarkar et al [72] used production and demand level parameters in developing a model in a three-echelon supply chain.…”

“…Another parameter in the study of Sarkar et al [18] and Masudin et al [74], namely the production level, shows that the production level parameter's sensitivity increases gradually with the total cost. Saga et al (2019) found a sensitivity test on energy loss related to carbon emissions released to increase the total cost. Moreover, Sarkar et al [72] analyzed the sensitivity to determine changes in the total cost of the supplier's carbon emission cost parameters and factory carbon emission costs.…”

Derivation of closed-form expression for optimal base stock level considering partial backorder, deterministic demand, and stochastic supply disruption

“…Relaxing the assumptions of fixed ordering cost and vendor's fixed set up cost, Jauhari and Saga (2017) considered fuzzy ordering cost and reducible setup cost. Besides, considering the impact of carbon incentive and penalty policy, Saga et al (2019) determined the optimal inventory decisions under the constrained service level. Fathalizadeh et al (2019) considered the effect of product deterioration and the stochastic inflation rate to determine the optimal inventory policy.…”

“…Because the retailer's interest is to minimize the total costs per day, the renewal reward theorem is used to formulate the retailer's expected cost per day function (Ross, 1996). The length of a renewal cycle is the interval between the occurrences of two consecutive disruptions, as seen in Figure 1.…”