Mohammad Saeed Jabalameli

Prof. Mohammad Saeed Jabalameli


Research Focus & Metrics

Academic Career Length

20Years (2007-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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23 July 2020 in International Journal of Production Research
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Journal Article
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FSFatemeh Sabouhi
Fatemeh Sabouhi
MJMohammad Saeed Jabalameli
Mohammad Saeed Jabalameli
AJArmin Jabbarzadeh
Armin Jabbarzadeh
BFBehnam Fahimnia
Behnam Fahimnia
We present a stochastic optimisation model that can be used to design a resilient supply chain operating under random disruptions. The model aims to determine sourcing and network design decisions that minimise the expected total cost while ensuring that the minimum customer service level is achieved. The proposed model incorporates several resilience strategies including multiple sourcing, multiple transport routes, considering backup suppliers, adding extra production capacities, as well as lateral transshipment and direct shipment. A multi-cut L-shaped solution approach is developed to solve the proposed model. Data from a real case problem in the paint industry is utilised to test the model and solution approach. Important managerial insights are obtained from the case study. Our analyses focus on (1) exploring the relationship between supply chain cost and customer service level, (2) examining the impacts of different types of disruptions on the total cost, (3) evaluating the utility of resilience strategies, (4) investigating the benefits of the proposed solution approach to solve problems of different sizes and (5) benchmarking the performance of the proposed stochastic programming approach.

22 February 2007 in The International Journal of Advanced Manufacturing Technology
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MJMohammad Saeed Jabalameli
Mohammad Saeed Jabalameli
JAJamal Arkat
Jamal Arkat

21 November 2012 in The International Journal of Advanced Manufacturing Technology
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NGNader Ghffarinasab
Nader Ghffarinasab
MJMohammad Saeed Jabalameli
Mohammad Saeed Jabalameli
MAMir Bahador Aryanezhad
Mir Bahador Aryanezhad
AMAhmad Makui
Ahmad Makui

7 September 2014 in Networks and Spatial Economics
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DSDavood Shishebori
Davood Shishebori
LSLawrence V. Snyder
Lawrence V. Snyder
MJMohammad Saeed Jabalameli
Mohammad Saeed Jabalameli

1 June 2023 in Kybernetes
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Journal Article
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SKSareh Khazaeli
Sareh Khazaeli
MJMohammad Saeed Jabalameli
Mohammad Saeed Jabalameli
HSHadi Sahebi
Hadi Sahebi
Purpose: Due to the importance of quality to customers, this study considers criteria of quality and profit and optimizes both in a multi-echelon cold chain of perishable agricultural products whose quality immediately begins to deteriorate after harvest. The two objectives of the proposed cold chain are to maximize profit and quality. Since postharvest quality loss in the supply chain depends on various decisions and factors, in addition to strategic decisions, the authors consider the temperature setting in refrigerated facilities and transportation vehicles due to the unfixed shelf life of the products which is related to the temperature found by Arrhenius formula.Design/methodology/approach: The authors use bi-objective mixed-integer nonlinear programming to design a four-echelon supply chain. The authors integrate the supply chain echelons to detect the sources and factors of quality loss. The four echelons include supply, processing, storage and customer. The decisions, including facility location, assigning nodes of each echelon to corresponding nodes from the adjacent echelon, allocation of vehicles to transport the products from farms to wholesalers, processing selection, and temperature setting in refrigerated facilities, are made in an integrated way. Model verification and validation in the case study are done based on three perishable herbal plants.Findings: The model obtains a 29% profit against a total cost of 71 and 93% of original quality of the crops is maintained, indicating a 7% quality loss. The final quality of 93% is the result of making a US$6m investment in the supply chain, including the procurement of high-quality raw materials; facility establishment; high-speed, high-capacity vehicles; location assignment; processing selection and refrigeration equipment in the storage and transportation systems, helping to maximize both the final quality of the products and the total profit.Research limitations/implications: The proposed supply chain model should help managers with modeling decisions, especially when it comes to cold chains for agricultural products. The model yields these results – optimal location-allocation decisions for the facilities to minimize distances between the network nodes, which save time and maintain the majority of the products’ original quality; choosing the most appropriate processing method, which reduces the perishability rate; providing high-capacity, high-speed vehicles in the logistics system, which minimizes transportation costs and maximizes the quality; and setting the right temperature in the refrigerated facilities, which mitigates the postharvest decay reaction rate of the products.Practical implications: Comparison of the results of the present research with those of the traditional chain (obtained through experts) shows that since the designed chain increases the profit as well as the final quality, it has benefits for the main chain stakeholders, which are customers of agricultural products. This study model is expected to have a positive impact on the environment by placing strong emphasis on quality and preventing excessive waste generation and air pollution by imposing a financial penalty on extra demand production.Social implications: Since profit and quality of the final product are two important factors in all cultures and communities, the proposed supply chain model can be used in any food industry around the world. Applying the proposed model induces growth in local industries and promotes the culture of prioritizing quality in societies.Originality/value: To the best of the authors’ knowledge, this is the first research on a bi-objective four-echelon (supply, processing, storage and customer) postharvest supply chain for agricultural products including that integrates transportation logistics and considers the deterioration rate of products as a time-dependent variable at different levels of decision-making.