DATA SET - D-CFLP & D-CFLP-NR

DATA SET - D-CFLP & D-CFLP-NR

Tores-Soto, J. E. and Uster, H., “Dynamic Demand Capacitated Facility Location Problems with and without Relocation,” International Journal of Production Research, Vol. 49/13, pp. 3979-4005, 2011.

Word File Version

Computation of Random Data: Details about generating random test instances.

Total Demand of Customers

Coordinates: For each customer , we generate a pair of coordinates from a discrete uniform distribution, from and from .
Regions: Each customer is assigned to a region according to its x-coordinate, i.e., region A in , region B in , and region C in .
Total Demand Patterns: To generate each demand structure, first we define a non-negative base value, , for each region, . We define and for . The demand in the first period for each customer location is randomly generated from a discrete uniform distribution , truncating the value towards zero.

For and , we define non-negative scalars and to generate a random number, , from a uniform distribution ; then for , the demand for each customer location is randomly generated from a discrete uniform distribution , truncating the value towards zero.

For , we evenly divide the length of the time horizon in three intervals, say ; ; and . We define the values of and to generate the random number, , in each interval. For , the demand for each customer location is randomly generated from a discrete uniform distribution ; for , from a discrete uniform distribution ; and for , from a discrete uniform distribution .

The following are the values used to generate the demand of customers:

Test Instances:

Data sets for D-CFLP:

	D-CFLP Increasing Demand
	Parameters						Parameters
Cluster			p %	f		Cluster			p %	f
1	50	5	5	U[100000,	150000]	7	100	5	5	U[100000,	150000]
	50	5	10	U[100000,	150000]		100	5	10	U[100000,	150000]
	50	5	15	U[100000,	150000]		100	5	15	U[100000,	150000]
2	50	5	5	U[200000,	250000]	8	100	5	5	U[200000,	250000]
	50	5	10	U[200000,	250000]		100	5	10	U[200000,	250000]
	50	5	15	U[200000,	250000]		100	5	15	U[200000,	250000]
3	50	5	5	U[300000,	350000]	9	100	5	5	U[300000,	350000]
	50	5	10	U[300000,	350000]		100	5	10	U[300000,	350000]
	50	5	15	U[300000,	350000]		100	5	15	U[300000,	350000]
4	50	10	5	U[100000,	150000]	10	100	10	5	U[100000,	150000]
	50	10	10	U[100000,	150000]		100	10	10	U[100000,	150000]
	50	10	15	U[100000,	150000]		100	10	15	U[100000,	150000]
5	50	10	5	U[200000,	250000]	11	100	10	5	U[200000,	250000]
	50	10	10	U[200000,	250000]		100	10	10	U[200000,	250000]
	50	10	15	U[200000,	250000]		100	10	15	U[200000,	250000]
6	50	10	5	U[300000,	350000]	12	100	10	5	U[300000,	350000]
	50	10	10	U[300000,	350000]		100	10	10	U[300000,	350000]
	50	10	15	U[300000,	350000]		100	10	15	U[300000,	350000]

	D-CFLP Decreasing Demand
	Parameters						Parameters
Cluster			p %	f		Cluster			p %	f
1	50	5	5	U[100000,	150000]	7	100	5	5	U[100000,	150000]
	50	5	10	U[100000,	150000]		100	5	10	U[100000,	150000]
	50	5	15	U[100000,	150000]		100	5	15	U[100000,	150000]
2	50	5	5	U[200000,	250000]	8	100	5	5	U[200000,	250000]
	50	5	10	U[200000,	250000]		100	5	10	U[200000,	250000]
	50	5	15	U[200000,	250000]		100	5	15	U[200000,	250000]
3	50	5	5	U[300000,	350000]	9	100	5	5	U[300000,	350000]
	50	5	10	U[300000,	350000]		100	5	10	U[300000,	350000]
	50	5	15	U[300000,	350000]		100	5	15	U[300000,	350000]
4	50	10	5	U[100000,	150000]	10	100	10	5	U[100000,	150000]
	50	10	10	U[100000,	150000]		100	10	10	U[100000,	150000]
	50	10	15	U[100000,	150000]		100	10	15	U[100000,	150000]
5	50	10	5	U[200000,	250000]	11	100	10	5	U[200000,	250000]
	50	10	10	U[200000,	250000]		100	10	10	U[200000,	250000]
	50	10	15	U[200000,	250000]		100	10	15	U[200000,	250000]
6	50	10	5	U[300000,	350000]	12	100	10	5	U[300000,	350000]
	50	10	10	U[300000,	350000]		100	10	10	U[300000,	350000]
	50	10	15	U[300000,	350000]		100	10	15	U[300000,	350000]

	D-CFLP Steady Demand
	Parameters						Parameters
Cluster			p %	f		Cluster			p %	f
1	50	5	5	U[100000,	150000]	7	100	5	5	U[100000,	150000]
	50	5	10	U[100000,	150000]		100	5	10	U[100000,	150000]
	50	5	15	U[100000,	150000]		100	5	15	U[100000,	150000]
2	50	5	5	U[200000,	250000]	8	100	5	5	U[200000,	250000]
	50	5	10	U[200000,	250000]		100	5	10	U[200000,	250000]
	50	5	15	U[200000,	250000]		100	5	15	U[200000,	250000]
3	50	5	5	U[300000,	350000]	9	100	5	5	U[300000,	350000]
	50	5	10	U[300000,	350000]		100	5	10	U[300000,	350000]
	50	5	15	U[300000,	350000]		100	5	15	U[300000,	350000]
4	50	10	5	U[100000,	150000]	10	100	10	5	U[100000,	150000]
	50	10	10	U[100000,	150000]		100	10	10	U[100000,	150000]
	50	10	15	U[100000,	150000]		100	10	15	U[100000,	150000]
5	50	10	5	U[200000,	250000]	11	100	10	5	U[200000,	250000]
	50	10	10	U[200000,	250000]		100	10	10	U[200000,	250000]
	50	10	15	U[200000,	250000]		100	10	15	U[200000,	250000]
6	50	10	5	U[300000,	350000]	12	100	10	5	U[300000,	350000]
	50	10	10	U[300000,	350000]		100	10	10	U[300000,	350000]
	50	10	15	U[300000,	350000]		100	10	15	U[300000,	350000]

Each data set has 360 files arranged into 12 zip files, one for each cluster. Each cluster contains 3 classes, and each class contains 10 instances.

Data set for D-CFLP-NR:

	D-CFLP-NR Increasing Demand
	Parameters						Parameters
Cluster			p %	f		Cluster			p %	f
1	50	5	15	U[100000,	150000]	5	150	5	15	U[100000,	150000]
	50	5	15	U[200000,	250000]		150	5	15	U[200000,	250000]
	50	5	15	U[300000,	350000]		150	5	15	U[300000,	350000]
2	50	10	15	U[100000,	150000]	6	150	10	15	U[100000,	150000]
	50	10	15	U[200000,	250000]		150	10	15	U[200000,	250000]
	50	10	15	U[300000,	350000]		150	10	15	U[300000,	350000]
3	100	5	15	U[100000,	150000]	7	200	5	15	U[100000,	150000]
	100	5	15	U[200000,	250000]		200	5	15	U[200000,	250000]
	100	5	15	U[300000,	350000]		200	5	15	U[300000,	350000]
4	100	10	15	U[100000,	150000]	8	200	10	15	U[100000,	150000]
	100	10	15	U[200000,	250000]		200	10	15	U[200000,	250000]
	100	10	15	U[300000,	350000]		200	10	15	U[300000,	350000]

	D-CFLP-NR Decreasing Demand
	Parameters						Parameters
Cluster			p %	f		Cluster			p %	f
1	50	5	15	U[100000,	150000]	5	150	5	15	U[100000,	150000]
	50	5	15	U[200000,	250000]		150	5	15	U[200000,	250000]
	50	5	15	U[300000,	350000]		150	5	15	U[300000,	350000]
2	50	10	15	U[100000,	150000]	6	150	10	15	U[100000,	150000]
	50	10	15	U[200000,	250000]		150	10	15	U[200000,	250000]
	50	10	15	U[300000,	350000]		150	10	15	U[300000,	350000]
3	100	5	15	U[100000,	150000]	7	200	5	15	U[100000,	150000]
	100	5	15	U[200000,	250000]		200	5	15	U[200000,	250000]
	100	5	15	U[300000,	350000]		200	5	15	U[300000,	350000]
4	100	10	15	U[100000,	150000]	8	200	10	15	U[100000,	150000]
	100	10	15	U[200000,	250000]		200	10	15	U[200000,	250000]
	100	10	15	U[300000,	350000]		200	10	15	U[300000,	350000]

	D-CFLP-NR Steady Demand
	Parameters						Parameters
Cluster			p %	f		Cluster			p %	f
1	50	5	15	U[100000,	150000]	5	150	5	15	U[100000,	150000]
	50	5	15	U[200000,	250000]		150	5	15	U[200000,	250000]
	50	5	15	U[300000,	350000]		150	5	15	U[300000,	350000]
2	50	10	15	U[100000,	150000]	6	150	10	15	U[100000,	150000]
	50	10	15	U[200000,	250000]		150	10	15	U[200000,	250000]
	50	10	15	U[300000,	350000]		150	10	15	U[300000,	350000]
3	100	5	15	U[100000,	150000]	7	200	5	15	U[100000,	150000]
	100	5	15	U[200000,	250000]		200	5	15	U[200000,	250000]
	100	5	15	U[300000,	350000]		200	5	15	U[300000,	350000]
4	100	10	15	U[100000,	150000]	8	200	10	15	U[100000,	150000]
	100	10	15	U[200000,	250000]		200	10	15	U[200000,	250000]
	100	10	15	U[300000,	350000]		200	10	15	U[300000,	350000]

Each data set has 240 files arranged into 8 zip files, one for each cluster. Each cluster contains 3 classes, and each class contains 10 instances.

· Data Files and Format:

All data files are “*.txt” format.
For each instance, the file contains the following data:

Number of customer locations .
Number of facility locations .
Number of periods .
Expected number of facilities p %.
Coordinates: arranged in rows and 2 columns; each row corresponds to a customer location; the first and second columns correspond to the and coordinates respectively.
Capacity: arranged in rows and 1 column; each row corresponds to the capacity available at each facility location.
Demand: arranged in rows and columns; each row corresponds to a customer location; each column corresponds to the customer’s demand in each time period.
Transportation cost: arranged in blocks, one for each customer location; each block has rows and columns.
Fixed operating, opening, and closing (only for D-CFLP) costs: each file has rows and columns (for D-CFLP-NR the opening cost is arranged in rows and 1 column); each row corresponds to a facility location and each column to the fixed cost in each time period.

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