What is a p-median problem?
2.1 Introduction. The p-median problem is that of locating p facilities to minimize the demand weighted average distance between demand nodes and the nearest of the selected facilities. The problem dates back to the seminal work of Hakimi (1964, 1965).
What is p-median model?
The p-median is a location-allocation model that locates a given number p of facilities, and allocates demand nodes i to facilities j to minimize the total distance traveled by consumers to facilities (Hakimi, 1964, Revelle and Swain, 1970).
How do you find the factor rating method?
Factor Rating
- Determine relevant and important factors.
- Assign a weight to each factor, with all weights totaling 1.00.
- Determine common scale for all factors, usually 0 to 100.
- Score each alternative.
- Adjust score using weights (multiply factor weight by score factor); add up scores for each alternative.
What are the problems in facility location?
The facility location problem (FLP) seeks to locate a number of facilities to serve a number of customers; thus, there is a set of potential facility locations F; opening a facility at location has an associated nonnegative fixed cost and has either a limited or unlimited capacity of available supply.
What is a factor rating?
Factor rating is a procedure or technique to evaluate multiple alternatives based on a number of selected factors.
What is qualitative factor rating method?
Factor rating is a means of assigning quantitative values to all the factors related to each decision option and then getting a score to evaluate which option is suitable. In this way right priorities are kept in mind and constraints are also ruled out.
What kind of problem is the P median problem?
The p-median problem is a graph theory problem that was originally designed for, and has been extensively applied to, facility location. In this bibliography, we summarize the literature on solution methods for the uncapacitated and capacitated p-median problem on a graph or network. 1 Introduction
How is Lagrangian relaxation used to solve the P median problem?
The following is a decomposition of how the technique of Lagrangian relaxation was implemented to solve the P-Median problem: Step 1: Setting up: We remove constraint (b) and add the constraint and a vector of variables called Lagrange multipliers to the objective function.
How is the upperbound of the P-median function determined?
The upperbound can be determined by simply determining the location closest to each customer. The corresponding allocation variables(Y) are then set to 1 while all others are set to 0. We then evaluate the P-Median objective function as stated originally.