Mevlut Savas Bilican - Academia.edu (original) (raw)

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Papers by Mevlut Savas Bilican

As a project report, it is well written but not so clear and needs to be supported by some visual... more As a project report, it is well written but not so clear and needs to be supported by some visual materials.

Annals of operation research/Annals of operations research, Feb 3, 2024

This paper proposes a decision support system (DSS) for optimizing cargo composition, and resulti... more This paper proposes a decision support system (DSS) for optimizing cargo composition, and resulting stowage plan, in a containership of a shipping company in collaboration with en-route ports in the service. Due to considerable growth in transportation over years, an increasing number of containers are being handled by containerships, and ports consequently. Trade imbalances between regions and recent disruptions, such as LA/LB/Shanghai port congestion, blocking of Suez canal, drought in Panama canal, typhoons at ports, COVID-19 restrictions and the lack-and then oversupply of empty containers, have resulted in an accumulation of containers in exporting ports around the world. These factors have underscored the urgency of sustainability and circular economy within the shipping industry. The demand for container transportation is higher than the ship capacities in the recent times. In this regard, it is essential for shipping companies to generate a cargo composition plan for each service by selecting and transporting containers with relatively high financial returns, while offering a realistic stowage plan considering ship stability, capacity limitations and port operations. Ultimately, the selected containers should enable a ship stowage plan which keeps the ship seaworthy obeying complex stability considerations and minimizes the vessel stay at the ports, and port carbon emissions consequently, through efficient collaboration with en-route ports. This study provides a bi-level programming based DSS that selects the set of containers to be loaded at each port of service and generates a detailed stowage plan considering Disclaimer The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of any affiliated organization or government.

This paper proposes a decision support system (DSS) for optimizing cargo composition, and resulti... more This paper proposes a decision support system (DSS) for optimizing cargo composition, and resulting stowage plan, in a containership of a shipping company in collaboration with en-route ports in the service. Due to considerable growth in transportation over years, an increasing number of containers are being handled by containerships, and ports consequently. Trade imbalances between regions and recent disruptions, such as LA/LB/Shanghai port congestion, blocking of Suez canal, drought in Panama canal, typhoons at ports, COVID-19 restrictions and the lack-and then oversupply of empty containers, have resulted in an accumulation of containers in exporting ports around the world. These factors have underscored the urgency of sustainability and circular economy within the shipping industry. The demand for container transportation is higher than the ship capacities in the recent times. In this regard, it is essential for shipping companies to generate a cargo composition plan for each service by selecting and transporting containers with relatively high financial returns, while offering a realistic stowage plan considering ship stability, capacity limitations and port operations. Ultimately, the selected containers should enable a ship stowage plan which keeps the ship seaworthy obeying complex stability considerations and minimizes the vessel stay at the ports, and port carbon emissions consequently, through efficient collaboration with en-route ports. This study provides a bi-level programming based DSS that selects the set of containers to be loaded at each port of service and generates a detailed stowage plan considering Disclaimer The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of any affiliated organization or government.

IEEE Access, 2020

Owing to the significant increase in the volume of world trade, mega-container vessels are being ... more Owing to the significant increase in the volume of world trade, mega-container vessels are being used to meet transportation demands. As the size of the vessels increases, the loading sequence of containers onto the vessels presents an important challenge for planners. In this study, we consider the container stowage planning problem with stability constraints (e.g. shear force, bending moment, trim) and develop a mixed integer linear programming (MILP) formulation which generates load plans by minimizing total cost associated with the over-stows and trimming moments. Our study adopts a holistic perspective which encompasses several real-world features such as different container specifications, a round-robin tour of multiple ports, technical limitations related to stack weight, stress, and ballast tanks. We also propose a two-stage heuristic solution methodology that employs an integer programming (IP) formulation and then a swapping heuristic (SH) algorithm. This approach first acquires a lower bound on the total over-stow cost with the IP model, thereby creating an initial bay plan. Then, it applies the SH algorithm to this initial bay plan to minimize cost resulting from trimming moments. The efficiency of the MILP formulation and heuristic algorithm is investigated through numerical examples. The results have shown that the heuristic has greatly improved the solution times as well as the size of the solvable problems compared to the MILP formulation. In particular, the two-stage heuristic can solve all size problem instances within an average optimality gap of 0-25% in less than 8 minutes, whereas the MILP can only achieve an approximate optimality gap of 55-80% in 2 hours. INDEX TERMS Container stowage plan, mixed integer linear programming, over-stow, stability.

Operations Research for Military Organizations, 2019

The success of military operations mainly relies on the proper flow of the logistical supplies su... more The success of military operations mainly relies on the proper flow of the logistical supplies such as water, food, ammunition, etc. from source to the operation theater on time. There are special types of transportation vessels regarding the feature of supply. However, when transporting special material like ammunition, most navies usually prefer utilizing their own transportation capabilities since they require special treatment. For this reason, such material is carried in special boxes, called containers. To minimize the transportation cost and time, an efficient container stowage plan is necessary in terms of loading and unloading these containers. This chapter aims to develop a solution methodology to the problem with the focus on military logistics planning. For this purpose, the author develops a mathematical model that attempts to minimize the transportation time by creating proper loading and unloading sequence of containers to military cargo ships.

As a project report, it is well written but not so clear and needs to be supported by some visual... more As a project report, it is well written but not so clear and needs to be supported by some visual materials.

Annals of operation research/Annals of operations research, Feb 3, 2024

This paper proposes a decision support system (DSS) for optimizing cargo composition, and resulti... more This paper proposes a decision support system (DSS) for optimizing cargo composition, and resulting stowage plan, in a containership of a shipping company in collaboration with en-route ports in the service. Due to considerable growth in transportation over years, an increasing number of containers are being handled by containerships, and ports consequently. Trade imbalances between regions and recent disruptions, such as LA/LB/Shanghai port congestion, blocking of Suez canal, drought in Panama canal, typhoons at ports, COVID-19 restrictions and the lack-and then oversupply of empty containers, have resulted in an accumulation of containers in exporting ports around the world. These factors have underscored the urgency of sustainability and circular economy within the shipping industry. The demand for container transportation is higher than the ship capacities in the recent times. In this regard, it is essential for shipping companies to generate a cargo composition plan for each service by selecting and transporting containers with relatively high financial returns, while offering a realistic stowage plan considering ship stability, capacity limitations and port operations. Ultimately, the selected containers should enable a ship stowage plan which keeps the ship seaworthy obeying complex stability considerations and minimizes the vessel stay at the ports, and port carbon emissions consequently, through efficient collaboration with en-route ports. This study provides a bi-level programming based DSS that selects the set of containers to be loaded at each port of service and generates a detailed stowage plan considering Disclaimer The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of any affiliated organization or government.

This paper proposes a decision support system (DSS) for optimizing cargo composition, and resulti... more This paper proposes a decision support system (DSS) for optimizing cargo composition, and resulting stowage plan, in a containership of a shipping company in collaboration with en-route ports in the service. Due to considerable growth in transportation over years, an increasing number of containers are being handled by containerships, and ports consequently. Trade imbalances between regions and recent disruptions, such as LA/LB/Shanghai port congestion, blocking of Suez canal, drought in Panama canal, typhoons at ports, COVID-19 restrictions and the lack-and then oversupply of empty containers, have resulted in an accumulation of containers in exporting ports around the world. These factors have underscored the urgency of sustainability and circular economy within the shipping industry. The demand for container transportation is higher than the ship capacities in the recent times. In this regard, it is essential for shipping companies to generate a cargo composition plan for each service by selecting and transporting containers with relatively high financial returns, while offering a realistic stowage plan considering ship stability, capacity limitations and port operations. Ultimately, the selected containers should enable a ship stowage plan which keeps the ship seaworthy obeying complex stability considerations and minimizes the vessel stay at the ports, and port carbon emissions consequently, through efficient collaboration with en-route ports. This study provides a bi-level programming based DSS that selects the set of containers to be loaded at each port of service and generates a detailed stowage plan considering Disclaimer The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of any affiliated organization or government.

IEEE Access, 2020

Owing to the significant increase in the volume of world trade, mega-container vessels are being ... more Owing to the significant increase in the volume of world trade, mega-container vessels are being used to meet transportation demands. As the size of the vessels increases, the loading sequence of containers onto the vessels presents an important challenge for planners. In this study, we consider the container stowage planning problem with stability constraints (e.g. shear force, bending moment, trim) and develop a mixed integer linear programming (MILP) formulation which generates load plans by minimizing total cost associated with the over-stows and trimming moments. Our study adopts a holistic perspective which encompasses several real-world features such as different container specifications, a round-robin tour of multiple ports, technical limitations related to stack weight, stress, and ballast tanks. We also propose a two-stage heuristic solution methodology that employs an integer programming (IP) formulation and then a swapping heuristic (SH) algorithm. This approach first acquires a lower bound on the total over-stow cost with the IP model, thereby creating an initial bay plan. Then, it applies the SH algorithm to this initial bay plan to minimize cost resulting from trimming moments. The efficiency of the MILP formulation and heuristic algorithm is investigated through numerical examples. The results have shown that the heuristic has greatly improved the solution times as well as the size of the solvable problems compared to the MILP formulation. In particular, the two-stage heuristic can solve all size problem instances within an average optimality gap of 0-25% in less than 8 minutes, whereas the MILP can only achieve an approximate optimality gap of 55-80% in 2 hours. INDEX TERMS Container stowage plan, mixed integer linear programming, over-stow, stability.

Operations Research for Military Organizations, 2019

The success of military operations mainly relies on the proper flow of the logistical supplies su... more The success of military operations mainly relies on the proper flow of the logistical supplies such as water, food, ammunition, etc. from source to the operation theater on time. There are special types of transportation vessels regarding the feature of supply. However, when transporting special material like ammunition, most navies usually prefer utilizing their own transportation capabilities since they require special treatment. For this reason, such material is carried in special boxes, called containers. To minimize the transportation cost and time, an efficient container stowage plan is necessary in terms of loading and unloading these containers. This chapter aims to develop a solution methodology to the problem with the focus on military logistics planning. For this purpose, the author develops a mathematical model that attempts to minimize the transportation time by creating proper loading and unloading sequence of containers to military cargo ships.