Durchschnittlicher Fortschritt
Empfohlene Karteikarten-Sets
Karteikarten im Karteikarten-Set
Noch nicht gestartet (15)
LP approach consits of 2 phases. Which ones?
1. Modelling phase
2. Solution phase
Give the 3 steps in the modelling phase.
1. Decisions (decision variables)
2. Objective --> We want to optimize the objective function
3. Constraints
What is the difference between feasible and infeasible solution?
A feasible solution is one that satisfies all defined constraints and requirements. A solution is infeasible when no combination of decision variable values can satisfy the entire set of requirements and constraints.
What is the difference between binding and non-binding?
If your answer is equal to the Right Hand Side (RHS) of the inequality, then the constraint is BINDING. If your answer is not equal to the RHS of the inequality, then the constraint is NON- BINDING.
(If shadow price = 0 then it is binding)
What is a reduntant constraint?
A Redundant Constraint is defined as a constraint that does not remove any degree of freedom when added.
Transportation Mix
A network which consists of a set of nodes and a set of arcs.
EFT and EFT basics
1. EFT = EST + D
2. Activities without immediate predecessors; EST = 0
3. Activities with immediate predecessor; EST = maximum EFT
LFST and LFT basics
1. LST = LFT - D
2. Activities without an immediate successor; LFT = minimum completion time
3. Activities with immediate successor; LFT = minimum LST
For all activities what is slack equal to?
S = LST - EST and equivalently:
S = LFT - EFT
The critical path is ...
The critical path (or paths) is the longest path (in time) from Start to Finish; it indicates the minimum time necessary to complete the entire project.
Summary of a network flow model:
1. Variables: flows on arcs + sketch the problem
2. Objective: minimize the total costs
3. Constraints: a) Capacity (one for each arc) b) flow balance: supply + inflow = demand + outflow
Specials situations in the basics of LP
1. Reduntant constraints
2. Multiple optimal solutions
3. Empty feasible regions
Expand on the special situation of reduntant constraints.
Has no role in determining feasible region
Expand on the special situation of multiple optimal solutions.
More than one feasible points that max or min the solution
Expand on the special situation of empty feasible regions.
No values for decision variables that satisfy constraints at the same time