scholarly journals Scheduling a Dynamic Aircraft Repair Shop with Limited Repair Resources

2013 ◽  
Vol 47 ◽  
pp. 35-70 ◽  
Author(s):  
M. Aramon Bajestani ◽  
J. C. Beck
Keyword(s):  
Benders Decomposition ◽  
Programming Model ◽  
Mixed Integer ◽  
Repair Shop ◽  
Repair Capacity ◽  
Full Complement ◽  
Changes Over Time ◽  
Specific Number ◽  
Schedule Repair

We address a dynamic repair shop scheduling problem in the context of military aircraft fleet management where the goal is to maintain a full complement of aircraft over the long-term. A number of flights, each with a requirement for a specific number and type of aircraft, are already scheduled over a long horizon. We need to assign aircraft to flights and schedule repair activities while considering the flights requirements, repair capacity, and aircraft failures. The number of aircraft awaiting repair dynamically changes over time due to failures and it is therefore necessary to rebuild the repair schedule online. To solve the problem, we view the dynamic repair shop as successive static repair scheduling sub-problems over shorter time periods. We propose a complete approach based on the logic-based Benders decomposition to solve the static sub-problems, and design different rescheduling policies to schedule the dynamic repair shop. Computational experiments demonstrate that the Benders model is able to find and prove optimal solutions on average four times faster than a mixed integer programming model. The rescheduling approach having both aspects of scheduling over a longer horizon and quickly adjusting the schedule increases aircraft available in the long term by 10% compared to the approaches having either one of the aspects alone.

scholarly journals Flow Merging and Hub Route Optimization in Collaborative Transportation

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Kerui Weng ◽  
Zi-hao Xu
Keyword(s):  
Integer Programming ◽  
Lagrangian Relaxation ◽  
Benders Decomposition ◽  
Programming Model ◽  
Route Optimization ◽  
Mixed Integer ◽  
Routing Problem ◽  
Fixed Charges ◽  
Postal Services ◽  
Cost Discount

This paper studies the optimal hub routing problem of merged tasks in collaborative transportation. This problem allows all carriers’ transportation tasks to reach the destinations optionally passing through 0, 1, or 2 hubs within limited distance, while a cost discount on arcs in the hub route could be acquired after paying fixed charges. The problem arises in the application of logistics, postal services, airline transportation, and so forth. We formulate the problem as a mixed-integer programming model, and provide two heuristic approaches, respectively, based on Lagrangian relaxation and Benders decomposition. Computational experiments show that the algorithms work well.

scholarly journals The Nutritious Supply Chain: Optimizing Humanitarian Food Assistance

2021 ◽  
pp. ijoo.2019.0047
Author(s):  
Koen Peters ◽  
Sérgio Silva ◽  
Rui Gonçalves ◽  
Mirjana Kavelj ◽  
Hein Fleuren ◽  
...  
Keyword(s):  
Supply Chain ◽  
Programming Model ◽  
Food Assistance ◽  
Decision Makers ◽  
Mixed Integer ◽  
Sourcing Strategies ◽  
Humanitarian Agency ◽  
Operational Excellence ◽  
Functional Areas

The World Food Programme (WFP) is the largest humanitarian agency fighting hunger worldwide, reaching approximately 90 million people with food assistance across 80 countries each year. To deal with the operational complexities inherent in its mandate, WFP has been developing tools to assist its decision makers with integrating supply chain decisions across departments and functional areas. This paper describes a mixed integer linear programming model that simultaneously optimizes the food basket to be delivered, the sourcing plan, the delivery plan, and the transfer modality of a long-term recovery operation for each month in a predefined time horizon. By connecting traditional supply chain elements to nutritional objectives, we are able to make significant breakthroughs in the operational excellence of WFP’s most complex operations. We show three examples of how the optimization model is used to support operations: (1) to reduce the operational costs in Iraq by 12% without compromising the nutritional value supplied, (2) to manage the scaling-up of the Yemen operation from three to six million beneficiaries, and (3) to identify sourcing strategies during the El Niño drought of 2016.

scholarly journals Sequential Model for Long-Term Planning of Building Renewal and Capital Improvement

2021 ◽  
Vol 13 (17) ◽  
pp. 9575
Author(s):  
Robert Bucoń ◽  
Agata Czarnigowska
Keyword(s):  
Programming Model ◽  
Residential Buildings ◽  
Planning Horizon ◽  
Mixed Integer ◽  
Building Performance ◽  
Optimal Sequence ◽  
Specific Order ◽  
Improvement Measures ◽  
Mutually Independent

The paper puts forward a mixed integer linear programming model to support the long-term planning and budgeting for renewal and capital improvements of residential buildings, i.e., to select the optimal sequence of repair and improvement actions over a predefined planning horizon. The input is provided by the evaluation of the building performance according to a set of criteria. Then a set of possible repairs, replacements and improvements needs to be proposed together with the estimates of their cost and benefits; the latter are expressed by increments of building performance ratings according to predefined criteria. The renewal and modernization measures are not mutually independent: at least some of them are complementary and should be carried out in a specific order. The optimization problem was to define the order of renewal/improvement measures resulting with the highest benefits available within the budget, or to achieve the required levels of building performance at the lowest cost. A unique feature of the model is the approach to the constraints on sequential relationships between the measures and to their selection. The model can be used to construct long-term renewal and capital improvement plans.

scholarly journals Estimating the farm-level economic costs of spring cropping to manage Alopecurus myosuroides (black-grass) in UK agriculture

2019 ◽  
Vol 157 (04) ◽  
pp. 318-332
Author(s):  
K. Ahodo ◽  
D. Oglethorpe ◽  
H. L. Hicks ◽  
R. P. Freckleton
Keyword(s):  
Programming Model ◽  
Mixed Integer ◽  
Farm Size ◽  
Economic Modelling ◽  
Short Term ◽  
Trade Off ◽  
Farm Level ◽  
Alopecurus Myosuroides ◽  
Goal Programming Model

AbstractCrop rotation is a non-chemical strategy adopted by farmers to manage weeds. However, not all crops in a rotation are equally profitable. Thus, there is potentially a trade-off between the costs and benefits of this strategy. The objective of the current study is to quantify this trade-off for the rotational control of an important weed (Alopecurus myosuroides). Data from 745 farms were used to parameterize a farm-level mixed-integer goal-programming model of the economics of spring cropping for weed control in UK agriculture. On average, the short-term loss of profit from spring cropping is greater than the benefits in terms of reduced herbicide usage and yield increases. These costs are greater when weed densities are low, so that spring cropping is an expensive strategy in the early stages of an infestation. However, there is a great deal of farm-to-farm variation: factors such as soil type and farm size are important and the current study highlights that economic modelling at the farm level is important in enabling farmers to make informed decisions. In general, however, if spring cropping is to be a successful strategy then the benefits to farmers will be in terms of long-term reductions in weed densities, but this will be at the expense of short-term profitability.

Sign in / Sign up

Export Citation Format

Share Document