scholarly journals Optimization Approaches for Defining Storage Strategies in Maritime Container Terminals

2021 ◽  
Author(s):  
Daniela Ambrosino ◽  
Haoqi Xie
Keyword(s):  
Linear Programming ◽  
Programming Model ◽  
Container Terminals ◽  
Linear Programming Model ◽  
Primary Role ◽  
Solution Approach ◽  
Efficient Management ◽  
Import And Export ◽  
Land Space

Abstract In maritime container terminals, yards have a primary role in permitting the efficient management of import and export flows. In this work, a mixed 0/1 linear programming model and a heuristic approach are proposed for defining storage rules in order to minimize the space used in the export yard. The minimization of land space is pursued by defining the rules to allocate containers into the bay-locations of the yard, in such a way to minimise the number of bay-locations used and the empty slots within them. The main aim of this work is to propose a solution approach for permitting to the yard manager to compare yard storage strategies for different transport demands, in such a way to be able to evaluate and, eventually, change the storage strategy when the characteristics of the transport demand change. Computational experiments, based on both real instances and generated ones, are presented. All instances are derived by a case study related to an Italian terminal.

scholarly journals A Mixed Integer Linear Programming Model for the Optimization of Steel Waste Gases in Cogeneration: A Combined Coke Oven and Converter Gas Case Study

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3781
Author(s):  
Sergio García García ◽  
Vicente Rodríguez Montequín ◽  
Henar Morán Palacios ◽  
Adriano Mones Bayo
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Programming Model ◽  
Coke Oven ◽  
Linear Programming Model ◽  
Mixed Integer ◽  
Integer Linear Programming Model ◽  
Converter Gas

Off-gas is one of the by-products of the steelmaking process. Its potential energy can be transformed into heat and electricity by means of cogeneration. A case study using a coke oven and Linz–Donawitz converter gas is presented. This work addresses the gas allocation problem for a cogeneration system producing steam and electricity. In the studied facility, located in northern Spain, the annual production of the plant requires 95,000 MWh of electrical energy and 525,000 MWh of thermal energy. The installed electrical and thermal power is 20.4 MW and 81 MW, respectively. A mixed integer linear programming model is built to optimize gas allocation, thus maximizing its benefits. This model is applied to a 24-h scenario with real data from the plant, where gas allocation decision-making was performed by the plant operators. Application of the model generated profit in a scenario where there were losses, increasing benefits by 16.9%. A sensitivity analysis is also performed. The proposed model is useful not only from the perspective of daily plant operation but also as a tool to simulate different design scenarios, such as the capacity of gasholders.

scholarly journals Incorporating the Credit Constraint in a Linear Programming Model: A Case Study of a Rural Farmer in Zimbabwe

2013 ◽  
Vol 1 (2) ◽  
pp. 245-250
Author(s):  
Felix Majeke ◽  
Michael Ticharwa Mubvuma ◽  
Kasirayi Makaza
Keyword(s):  
Linear Programming ◽  
Programming Model ◽  
Linear Programming Model ◽  
Working Capital ◽  
Credit Constraint ◽  
Important Constraint ◽  
Model Solutions ◽  
Lp Model

The available working capital required to finance purchase of inputs on a farm like seeds for instance, can be an important constraint on a farm. Some working capital may be available from the farm family‘s savings. The farmer may have an option for increasing his working capital by borrowing. In this study, a linear programming model was developed in order to determine the optimal crop combination for a rural farmer. The linear programming model incorporated the credit constraint. The objective was to maximize income. Crops considered were maize, soya beans, cotton and tobacco. Tobacco gained acreage by 291.33%.Soya beans and cotton lost acreage completely. Maize lost acreage by 73.5%. The optimal income increased from $9,877.00 to $22,774.60. The optimal income showed an improvement of 130.58% compared to the farmer‘s existing plan. The results show that LP model solutions are worthy implementing because they increase income.

Simultaneous scheduling of maintenance crew and maintenance tasks in bus operating companies: a case study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rodrigo Martins ◽  
Francisco Fernandes ◽  
Virginia Infante ◽  
Antonio R. Andrade
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Programming Model ◽  
Maintenance Scheduling ◽  
Linear Programming Model ◽  
Integer Linear Programming Model ◽  
Content Type ◽  
Maintenance Schedules ◽  
Operating Company

PurposeThe purpose of this paper is to describe an integer linear programming model to schedule the maintenance crew and the maintenance tasks in a bus operating company.Design/methodology/approachThe proposed methodology relies on an integer linear programming model that finds feasible maintenance schedules. It minimizes the costs associated with maintenance crew and the costs associated with unavailability. The model is applied in a real-world case study of a Portuguese bus operating company. A constructive heuristic approach is put forward, based on solving the maintenance scheduling problem for each bus separately.FindingsThe heuristic finds better solutions than the exact methods (based on branch-and-bound techniques) in a much lower computational time.Practical implicationsThe results suggest the relevance of such heuristic approaches for maintenance scheduling in practice.Originality/valueThis proposed model is an effective decision-making support method that provides feasible maintenance schedules for the maintenance technicians and for the maintenance tasks in a fleet of buses. It also complies with several operational, technical and labour constraints.

scholarly journals USTED: a methodology for a quantitative analysis of land use scenarios

1995 ◽  
Vol 43 (1) ◽  
pp. 5-18 ◽  
Author(s):  
J.J. Stoorvogel ◽  
R.A. Schipper ◽  
D.M. Jansen
Keyword(s):  
Land Use ◽  
Linear Programming ◽  
Agricultural Land ◽  
Programming Model ◽  
Computer Software ◽  
Simulation Models ◽  
Linear Programming Model ◽  
Chemical Compositions ◽  
Attribute Data

Scenarios are a useful tool to study the effects of changes in the socio-economic and/or biophysical environment on agricultural land use. For the analysis of these scenarios an operational methodology, USTED, has been developed. The methodology is based on a linear programming model in combination with GIS, crop growth simulation models, and expert systems. The data requirements include quantitative descriptions of land use systems and technologies, attribute data on such features as prices and chemical compositions, and georeferenced data on farms and soils. Sustainability is incorporated in the methodology by a limited number of quantified sustainability parameters. The linear programming model analyses, on the basis of different farm types, the effect of different scenarios on land use. Customized computer software (MODUS) is used to integrate the different models. The methodology is illustrated with a case study for the Neguev settlement in the Atlantic Zone of Costa Rica.

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