A bi-objective multi-echelon supply chain model with Pareto optimal points evaluation for perishable products under uncertainty

Gitinavard, Hossein; Ghodsypour, Seyed Hassan; Shirazi, Mohsen Akbarpour

doi:10.24200/sci.2018.5047.1060

Cited by 4 publications

(5 citation statements)

References 44 publications

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“…Constraint (12) guarantees that the demand for biofuel is to be provided in each period. Constraints ( 13) and (14) ensure that, at most, one bio-refinery and collection facility can be open at the same place. Constraint (15) represents that the initial inventory level in each facility is zero.…”

Section: Mathematical Modelmentioning

confidence: 99%

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A Robust Possibilistic Bi-Objective Mixed Integer Model for Green Biofuel Supply Chain Design under Uncertain Conditions

et al. 2022

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In recent years, concerns regarding issues such as climate change, greenhouse gas emissions, fossil reserve dependency, and petroleum price fluctuation have led countries to focus on renewable energies. Meanwhile, in developing countries, designing an appropriate biofuel supply chain network regarding environmental competencies is an important problem. This paper presents a new bi-objective mixed integer mathematical model aiming to minimize CO2 emission and total costs in the process of the biofuel supply chain, creating a suitable green supply chain network. In this respect, CO2 emission and biofuel demand are regarded as uncertain data to address the real complex cases. Moreover, the SAUGMECON approach was implemented to construct a single objective model, and the obtained Pareto optimal points were depicted and analyzed. Thereby, a robust possibilistic programming approach was implemented to the proposed model to handle existing imprecise data. Furthermore, the applicability and performance of the proposed model were demonstrated based on an experimental example. In this respect, the obtained results from the proposed robust possibilistic programming model were compared with its crisp form to show the robustness and reliability of the proposed uncertain mathematical model.

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Section: Mathematical Modelmentioning

confidence: 99%

“…Bai et al [12] developed a discretely constrained mathematical program with equilibrium constraints for competitive BSCN. Furthermore, some studies have focused on BSCNs under precise information [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

A Robust Possibilistic Bi-Objective Mixed Integer Model for Green Biofuel Supply Chain Design under Uncertain Conditions

et al. 2022

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“…A supply chain network system is full of uncertainties and variations, for example, demand uncertainty, lead time variability, supplier fault, which accordingly cause degradation of system performance [1,2]. If these variations and uncertainties amass up to a point, the supply chain network system may fail.…”

Section: Introductionmentioning

confidence: 99%

Applying a change-point control chart based on likelihood ratio to supply chain network monitoring

Zhong

Yang

et al. 2019

Scientia Iranica

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A supply chain network system is regarded as a serial-parallel multistage process; and the application of a change-point control chart based on likelihood ratio is explored to monitor this system. Firstly, state-space modeling is used to characterize complexities of the supply chain network system. Secondly, a change-point control chart based on likelihood ratio is used to trigger potential tardy orders in the system. Thirdly, a case study is illustrated to indicate that the change-point control chart can effectively signal mean shift in completion time of one order in one stage, and can accurately estimate the change point and the out-of-control stage in term of the performance indexes. In detail, when the mean shift is relatively small, the change-point control chart can effectively identify it, and more accurately detect the change point and the out-of-control stage comparing with the traditional Shewhart control chart. We also investigate the effect of misspecified parameters of state space equations on performance of the change-point control chart. The results show that the performance of the change-point control chart can still maintain relatively stable. In general, the change-point control can effectively monitor the supply chain network system, and the monitoring effect is relatively stable.

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“…Literature survey reveals that there is a significant research gap between the old practices and new practices for handling the lot size problem of perishable goods. Available literature survey [13][14][15][16][17][18][19][20][21][22] in the domain of this area mainly focuses on the production and inventory of perishable products. Now, due to increasing global competitive environment, it is necessary to handle the perishable product with low cost and less environmental impact.…”

Section: Introductionmentioning

confidence: 99%

“…of time, each market not only maintain a safety stock i.e., minimum level of inventory but also inventory should not exceeds the maximum capacity and this constraint is expressed in equation(19).Number of FTL trucks transported from plant 'p' to cross-dock 'c' at period 't' is calculated by using equation of FTL trucks transported from cross-dock 'c' to market 'm' at period 't' is calculated by using equation(21). of HTL trucks transported from plant 'p' to cross-dock 'c' at period 't' is calculated by using equation(22).…”

mentioning

confidence: 99%

A holistic framework for lot sizing problem in fast-moving perishable products

Sinha

Anand

2018

Scientia Iranica

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One of the major challenges being faced by manufacturing companies today is the issue of addressing various aspects of perishable products in a supply chain environment. To address this issue, the integrated lot size problem for a perishable product has been investigated in the present work. The problem is modeled as a single vendor multiple buyer system. A variant of the truckload discount scheme is applied and the proposed model is formulated as a mixed integer program (MIP). The traditional warehouses are replaced by 'cross-docks' and situations in which, cross-docking would be more beneficial are highlighted. The problem of fleet selection is also addressed and various strategies to minimize the vendor cost are also highlighted for centralized and decentralized supply chains.Sensitivity analysis is then carried out on various input parameters such as setup cost at plant, variable transportation cost, fixed transportation cost, setup cost per order, holding cost and, lost cost, which underscores the significant impact of economies of scale in transportation on the total supply chain cost.Analysis of lead time-cost trade-off reveals that alternate modes of transportation could be explored, which significantly reduces the lead time of transportation, thereby minimizing the total supply chain cost.towards sustainability in the global competitive environment [2]. In the current times, the concept of SC network has been shifting from traditional SC environment. Nowadays, SC is an integral system of raw materials, material procurement, suppliers, manufacturing processes, assembly, dispatch, logistics, inventory, cross-docks, warehouses, end customers and, finally recycling of the product [3]. The SC environment is also defined as an effective management of all components / partners related to SC network which include transportation and replenishment of raw materials either inside the manufacturing shop floor or shipment of finished goods along with transportation decisions (mode of shipment, lot size and, fleet selection) for yielding competitive advantages for all individual components / partners [4-5] . SC network design mainly consists of three levels namely strategic, tactical and, operational decisions [6]. Strategic decisions mainly emphasize on production, assembly and, distribution to fulfill the demand of end customers. Tactical decisions describes the management policy for flow of materials, decisions related to various production level, assembly section, inventory control and, lot sizes. Decisions on operational level deals with scheduling of different operations of SC network for making responsive SC design including coordination in logistic network for assuring on time delivery of the product to the end customer at low cost with least environmental impact [7-8]. However, logistic network which is a part of green supply chain network is one of the major challenging tasks for every manufacturing industry.Moreover, perishability is one of the key issues in a supply chain environment. Integration of product...

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A bi-objective multi-echelon supply chain model with Pareto optimal points evaluation for perishable products under uncertainty

Cited by 4 publications

References 44 publications

A Robust Possibilistic Bi-Objective Mixed Integer Model for Green Biofuel Supply Chain Design under Uncertain Conditions

A Robust Possibilistic Bi-Objective Mixed Integer Model for Green Biofuel Supply Chain Design under Uncertain Conditions

Applying a change-point control chart based on likelihood ratio to supply chain network monitoring

A holistic framework for lot sizing problem in fast-moving perishable products

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