Colored Bin Packing: Online Algorithms and Lower Bounds
Abstract In the Colored Bin Packing problem a sequence of items of sizes up to 1 arrives to be packed into bins of unit capacity. Each item has one of at least two colors and an additional constraint is that we cannot pack two items of the same color next to each other in the same bin. The objective...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Böhm, Martin [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media New York 2016 |
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| Übergeordnetes Werk: |
Enthalten in: Algorithmica - Springer US, 1986, 80(2016), 1 vom: 17. Nov., Seite 155-184 |
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| Übergeordnetes Werk: |
volume:80 ; year:2016 ; number:1 ; day:17 ; month:11 ; pages:155-184 |
| Links: |
|---|
| DOI / URN: |
10.1007/s00453-016-0248-2 |
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| Katalog-ID: |
OLC2054851744 |
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| 520 | |a Abstract In the Colored Bin Packing problem a sequence of items of sizes up to 1 arrives to be packed into bins of unit capacity. Each item has one of at least two colors and an additional constraint is that we cannot pack two items of the same color next to each other in the same bin. The objective is to minimize the number of bins. In the important special case when all items have size zero, we characterize the optimal value to be equal to color discrepancy. As our main result, we give an (asymptotically) 1.5-competitive algorithm which is optimal. In fact, the algorithm always uses at most $$\lceil 1.5\cdot OPT \rceil $$ bins and we can force any deterministic online algorithm to use at least $$\lceil 1.5\cdot OPT \rceil $$ bins while the offline optimum is $$ OPT $$ for any value of $$ OPT \ge 2$$. In particular, the absolute competitive ratio of our algorithm is 5 / 3 and this is optimal. For items of arbitrary size we give a lower bound of 2.5 on the asymptotic competitive ratio of any online algorithm and an absolutely 3.5-competitive algorithm. When the items have sizes of at most 1 / d for a real $$d \ge 2$$ the asymptotic competitive ratio of our algorithm is $$1.5+d/(d-1)$$. We also show that classical algorithms First Fit, Best Fit and Worst Fit are not constant competitive, which holds already for three colors and small items. In the case of two colors—the Black and White Bin Packing problem—we give a lower bound of 2 on the asymptotic competitive ratio of any online algorithm when items have arbitrary size. We also prove that all Any Fit algorithms have the absolute competitive ratio 3. When the items have sizes of at most 1 / d for a real $$d \ge 2$$ we show that the Worst Fit algorithm is absolutely $$(1+d/(d-1))$$-competitive. | ||
| 650 | 4 | |a Online algorithms | |
| 650 | 4 | |a Bin packing | |
| 650 | 4 | |a Worst-case analysis | |
| 650 | 4 | |a Colored bin packing | |
| 650 | 4 | |a Black and white bin packing | |
| 700 | 1 | |a Dósa, György |4 aut | |
| 700 | 1 | |a Epstein, Leah |4 aut | |
| 700 | 1 | |a Sgall, Jiří |4 aut | |
| 700 | 1 | |a Veselý, Pavel |4 aut | |
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10.1007/s00453-016-0248-2 doi (DE-627)OLC2054851744 (DE-He213)s00453-016-0248-2-p DE-627 ger DE-627 rakwb eng 004 VZ 510 004 VZ Böhm, Martin verfasserin aut Colored Bin Packing: Online Algorithms and Lower Bounds 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2016 Abstract In the Colored Bin Packing problem a sequence of items of sizes up to 1 arrives to be packed into bins of unit capacity. Each item has one of at least two colors and an additional constraint is that we cannot pack two items of the same color next to each other in the same bin. The objective is to minimize the number of bins. In the important special case when all items have size zero, we characterize the optimal value to be equal to color discrepancy. As our main result, we give an (asymptotically) 1.5-competitive algorithm which is optimal. In fact, the algorithm always uses at most $$\lceil 1.5\cdot OPT \rceil $$ bins and we can force any deterministic online algorithm to use at least $$\lceil 1.5\cdot OPT \rceil $$ bins while the offline optimum is $$ OPT $$ for any value of $$ OPT \ge 2$$. In particular, the absolute competitive ratio of our algorithm is 5 / 3 and this is optimal. For items of arbitrary size we give a lower bound of 2.5 on the asymptotic competitive ratio of any online algorithm and an absolutely 3.5-competitive algorithm. When the items have sizes of at most 1 / d for a real $$d \ge 2$$ the asymptotic competitive ratio of our algorithm is $$1.5+d/(d-1)$$. We also show that classical algorithms First Fit, Best Fit and Worst Fit are not constant competitive, which holds already for three colors and small items. In the case of two colors—the Black and White Bin Packing problem—we give a lower bound of 2 on the asymptotic competitive ratio of any online algorithm when items have arbitrary size. We also prove that all Any Fit algorithms have the absolute competitive ratio 3. When the items have sizes of at most 1 / d for a real $$d \ge 2$$ we show that the Worst Fit algorithm is absolutely $$(1+d/(d-1))$$-competitive. Online algorithms Bin packing Worst-case analysis Colored bin packing Black and white bin packing Dósa, György aut Epstein, Leah aut Sgall, Jiří aut Veselý, Pavel aut Enthalten in Algorithmica Springer US, 1986 80(2016), 1 vom: 17. Nov., Seite 155-184 (DE-627)129197564 (DE-600)53958-2 (DE-576)014456958 0178-4617 nnns volume:80 year:2016 number:1 day:17 month:11 pages:155-184 https://doi.org/10.1007/s00453-016-0248-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_24 GBV_ILN_70 GBV_ILN_130 GBV_ILN_2018 GBV_ILN_4266 GBV_ILN_4318 GBV_ILN_4319 AR 80 2016 1 17 11 155-184 |
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10.1007/s00453-016-0248-2 doi (DE-627)OLC2054851744 (DE-He213)s00453-016-0248-2-p DE-627 ger DE-627 rakwb eng 004 VZ 510 004 VZ Böhm, Martin verfasserin aut Colored Bin Packing: Online Algorithms and Lower Bounds 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2016 Abstract In the Colored Bin Packing problem a sequence of items of sizes up to 1 arrives to be packed into bins of unit capacity. Each item has one of at least two colors and an additional constraint is that we cannot pack two items of the same color next to each other in the same bin. The objective is to minimize the number of bins. In the important special case when all items have size zero, we characterize the optimal value to be equal to color discrepancy. As our main result, we give an (asymptotically) 1.5-competitive algorithm which is optimal. In fact, the algorithm always uses at most $$\lceil 1.5\cdot OPT \rceil $$ bins and we can force any deterministic online algorithm to use at least $$\lceil 1.5\cdot OPT \rceil $$ bins while the offline optimum is $$ OPT $$ for any value of $$ OPT \ge 2$$. In particular, the absolute competitive ratio of our algorithm is 5 / 3 and this is optimal. For items of arbitrary size we give a lower bound of 2.5 on the asymptotic competitive ratio of any online algorithm and an absolutely 3.5-competitive algorithm. When the items have sizes of at most 1 / d for a real $$d \ge 2$$ the asymptotic competitive ratio of our algorithm is $$1.5+d/(d-1)$$. We also show that classical algorithms First Fit, Best Fit and Worst Fit are not constant competitive, which holds already for three colors and small items. In the case of two colors—the Black and White Bin Packing problem—we give a lower bound of 2 on the asymptotic competitive ratio of any online algorithm when items have arbitrary size. We also prove that all Any Fit algorithms have the absolute competitive ratio 3. When the items have sizes of at most 1 / d for a real $$d \ge 2$$ we show that the Worst Fit algorithm is absolutely $$(1+d/(d-1))$$-competitive. Online algorithms Bin packing Worst-case analysis Colored bin packing Black and white bin packing Dósa, György aut Epstein, Leah aut Sgall, Jiří aut Veselý, Pavel aut Enthalten in Algorithmica Springer US, 1986 80(2016), 1 vom: 17. Nov., Seite 155-184 (DE-627)129197564 (DE-600)53958-2 (DE-576)014456958 0178-4617 nnns volume:80 year:2016 number:1 day:17 month:11 pages:155-184 https://doi.org/10.1007/s00453-016-0248-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_24 GBV_ILN_70 GBV_ILN_130 GBV_ILN_2018 GBV_ILN_4266 GBV_ILN_4318 GBV_ILN_4319 AR 80 2016 1 17 11 155-184 |
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10.1007/s00453-016-0248-2 doi (DE-627)OLC2054851744 (DE-He213)s00453-016-0248-2-p DE-627 ger DE-627 rakwb eng 004 VZ 510 004 VZ Böhm, Martin verfasserin aut Colored Bin Packing: Online Algorithms and Lower Bounds 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2016 Abstract In the Colored Bin Packing problem a sequence of items of sizes up to 1 arrives to be packed into bins of unit capacity. Each item has one of at least two colors and an additional constraint is that we cannot pack two items of the same color next to each other in the same bin. The objective is to minimize the number of bins. In the important special case when all items have size zero, we characterize the optimal value to be equal to color discrepancy. As our main result, we give an (asymptotically) 1.5-competitive algorithm which is optimal. In fact, the algorithm always uses at most $$\lceil 1.5\cdot OPT \rceil $$ bins and we can force any deterministic online algorithm to use at least $$\lceil 1.5\cdot OPT \rceil $$ bins while the offline optimum is $$ OPT $$ for any value of $$ OPT \ge 2$$. In particular, the absolute competitive ratio of our algorithm is 5 / 3 and this is optimal. For items of arbitrary size we give a lower bound of 2.5 on the asymptotic competitive ratio of any online algorithm and an absolutely 3.5-competitive algorithm. When the items have sizes of at most 1 / d for a real $$d \ge 2$$ the asymptotic competitive ratio of our algorithm is $$1.5+d/(d-1)$$. We also show that classical algorithms First Fit, Best Fit and Worst Fit are not constant competitive, which holds already for three colors and small items. In the case of two colors—the Black and White Bin Packing problem—we give a lower bound of 2 on the asymptotic competitive ratio of any online algorithm when items have arbitrary size. We also prove that all Any Fit algorithms have the absolute competitive ratio 3. When the items have sizes of at most 1 / d for a real $$d \ge 2$$ we show that the Worst Fit algorithm is absolutely $$(1+d/(d-1))$$-competitive. Online algorithms Bin packing Worst-case analysis Colored bin packing Black and white bin packing Dósa, György aut Epstein, Leah aut Sgall, Jiří aut Veselý, Pavel aut Enthalten in Algorithmica Springer US, 1986 80(2016), 1 vom: 17. Nov., Seite 155-184 (DE-627)129197564 (DE-600)53958-2 (DE-576)014456958 0178-4617 nnns volume:80 year:2016 number:1 day:17 month:11 pages:155-184 https://doi.org/10.1007/s00453-016-0248-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_24 GBV_ILN_70 GBV_ILN_130 GBV_ILN_2018 GBV_ILN_4266 GBV_ILN_4318 GBV_ILN_4319 AR 80 2016 1 17 11 155-184 |
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10.1007/s00453-016-0248-2 doi (DE-627)OLC2054851744 (DE-He213)s00453-016-0248-2-p DE-627 ger DE-627 rakwb eng 004 VZ 510 004 VZ Böhm, Martin verfasserin aut Colored Bin Packing: Online Algorithms and Lower Bounds 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2016 Abstract In the Colored Bin Packing problem a sequence of items of sizes up to 1 arrives to be packed into bins of unit capacity. Each item has one of at least two colors and an additional constraint is that we cannot pack two items of the same color next to each other in the same bin. The objective is to minimize the number of bins. In the important special case when all items have size zero, we characterize the optimal value to be equal to color discrepancy. As our main result, we give an (asymptotically) 1.5-competitive algorithm which is optimal. In fact, the algorithm always uses at most $$\lceil 1.5\cdot OPT \rceil $$ bins and we can force any deterministic online algorithm to use at least $$\lceil 1.5\cdot OPT \rceil $$ bins while the offline optimum is $$ OPT $$ for any value of $$ OPT \ge 2$$. In particular, the absolute competitive ratio of our algorithm is 5 / 3 and this is optimal. For items of arbitrary size we give a lower bound of 2.5 on the asymptotic competitive ratio of any online algorithm and an absolutely 3.5-competitive algorithm. When the items have sizes of at most 1 / d for a real $$d \ge 2$$ the asymptotic competitive ratio of our algorithm is $$1.5+d/(d-1)$$. We also show that classical algorithms First Fit, Best Fit and Worst Fit are not constant competitive, which holds already for three colors and small items. In the case of two colors—the Black and White Bin Packing problem—we give a lower bound of 2 on the asymptotic competitive ratio of any online algorithm when items have arbitrary size. We also prove that all Any Fit algorithms have the absolute competitive ratio 3. When the items have sizes of at most 1 / d for a real $$d \ge 2$$ we show that the Worst Fit algorithm is absolutely $$(1+d/(d-1))$$-competitive. Online algorithms Bin packing Worst-case analysis Colored bin packing Black and white bin packing Dósa, György aut Epstein, Leah aut Sgall, Jiří aut Veselý, Pavel aut Enthalten in Algorithmica Springer US, 1986 80(2016), 1 vom: 17. Nov., Seite 155-184 (DE-627)129197564 (DE-600)53958-2 (DE-576)014456958 0178-4617 nnns volume:80 year:2016 number:1 day:17 month:11 pages:155-184 https://doi.org/10.1007/s00453-016-0248-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_24 GBV_ILN_70 GBV_ILN_130 GBV_ILN_2018 GBV_ILN_4266 GBV_ILN_4318 GBV_ILN_4319 AR 80 2016 1 17 11 155-184 |
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10.1007/s00453-016-0248-2 doi (DE-627)OLC2054851744 (DE-He213)s00453-016-0248-2-p DE-627 ger DE-627 rakwb eng 004 VZ 510 004 VZ Böhm, Martin verfasserin aut Colored Bin Packing: Online Algorithms and Lower Bounds 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2016 Abstract In the Colored Bin Packing problem a sequence of items of sizes up to 1 arrives to be packed into bins of unit capacity. Each item has one of at least two colors and an additional constraint is that we cannot pack two items of the same color next to each other in the same bin. The objective is to minimize the number of bins. In the important special case when all items have size zero, we characterize the optimal value to be equal to color discrepancy. As our main result, we give an (asymptotically) 1.5-competitive algorithm which is optimal. In fact, the algorithm always uses at most $$\lceil 1.5\cdot OPT \rceil $$ bins and we can force any deterministic online algorithm to use at least $$\lceil 1.5\cdot OPT \rceil $$ bins while the offline optimum is $$ OPT $$ for any value of $$ OPT \ge 2$$. In particular, the absolute competitive ratio of our algorithm is 5 / 3 and this is optimal. For items of arbitrary size we give a lower bound of 2.5 on the asymptotic competitive ratio of any online algorithm and an absolutely 3.5-competitive algorithm. When the items have sizes of at most 1 / d for a real $$d \ge 2$$ the asymptotic competitive ratio of our algorithm is $$1.5+d/(d-1)$$. We also show that classical algorithms First Fit, Best Fit and Worst Fit are not constant competitive, which holds already for three colors and small items. In the case of two colors—the Black and White Bin Packing problem—we give a lower bound of 2 on the asymptotic competitive ratio of any online algorithm when items have arbitrary size. We also prove that all Any Fit algorithms have the absolute competitive ratio 3. When the items have sizes of at most 1 / d for a real $$d \ge 2$$ we show that the Worst Fit algorithm is absolutely $$(1+d/(d-1))$$-competitive. Online algorithms Bin packing Worst-case analysis Colored bin packing Black and white bin packing Dósa, György aut Epstein, Leah aut Sgall, Jiří aut Veselý, Pavel aut Enthalten in Algorithmica Springer US, 1986 80(2016), 1 vom: 17. Nov., Seite 155-184 (DE-627)129197564 (DE-600)53958-2 (DE-576)014456958 0178-4617 nnns volume:80 year:2016 number:1 day:17 month:11 pages:155-184 https://doi.org/10.1007/s00453-016-0248-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_24 GBV_ILN_70 GBV_ILN_130 GBV_ILN_2018 GBV_ILN_4266 GBV_ILN_4318 GBV_ILN_4319 AR 80 2016 1 17 11 155-184 |
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colored bin packing: online algorithms and lower bounds |
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Colored Bin Packing: Online Algorithms and Lower Bounds |
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Abstract In the Colored Bin Packing problem a sequence of items of sizes up to 1 arrives to be packed into bins of unit capacity. Each item has one of at least two colors and an additional constraint is that we cannot pack two items of the same color next to each other in the same bin. The objective is to minimize the number of bins. In the important special case when all items have size zero, we characterize the optimal value to be equal to color discrepancy. As our main result, we give an (asymptotically) 1.5-competitive algorithm which is optimal. In fact, the algorithm always uses at most $$\lceil 1.5\cdot OPT \rceil $$ bins and we can force any deterministic online algorithm to use at least $$\lceil 1.5\cdot OPT \rceil $$ bins while the offline optimum is $$ OPT $$ for any value of $$ OPT \ge 2$$. In particular, the absolute competitive ratio of our algorithm is 5 / 3 and this is optimal. For items of arbitrary size we give a lower bound of 2.5 on the asymptotic competitive ratio of any online algorithm and an absolutely 3.5-competitive algorithm. When the items have sizes of at most 1 / d for a real $$d \ge 2$$ the asymptotic competitive ratio of our algorithm is $$1.5+d/(d-1)$$. We also show that classical algorithms First Fit, Best Fit and Worst Fit are not constant competitive, which holds already for three colors and small items. In the case of two colors—the Black and White Bin Packing problem—we give a lower bound of 2 on the asymptotic competitive ratio of any online algorithm when items have arbitrary size. We also prove that all Any Fit algorithms have the absolute competitive ratio 3. When the items have sizes of at most 1 / d for a real $$d \ge 2$$ we show that the Worst Fit algorithm is absolutely $$(1+d/(d-1))$$-competitive. © Springer Science+Business Media New York 2016 |
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Abstract In the Colored Bin Packing problem a sequence of items of sizes up to 1 arrives to be packed into bins of unit capacity. Each item has one of at least two colors and an additional constraint is that we cannot pack two items of the same color next to each other in the same bin. The objective is to minimize the number of bins. In the important special case when all items have size zero, we characterize the optimal value to be equal to color discrepancy. As our main result, we give an (asymptotically) 1.5-competitive algorithm which is optimal. In fact, the algorithm always uses at most $$\lceil 1.5\cdot OPT \rceil $$ bins and we can force any deterministic online algorithm to use at least $$\lceil 1.5\cdot OPT \rceil $$ bins while the offline optimum is $$ OPT $$ for any value of $$ OPT \ge 2$$. In particular, the absolute competitive ratio of our algorithm is 5 / 3 and this is optimal. For items of arbitrary size we give a lower bound of 2.5 on the asymptotic competitive ratio of any online algorithm and an absolutely 3.5-competitive algorithm. When the items have sizes of at most 1 / d for a real $$d \ge 2$$ the asymptotic competitive ratio of our algorithm is $$1.5+d/(d-1)$$. We also show that classical algorithms First Fit, Best Fit and Worst Fit are not constant competitive, which holds already for three colors and small items. In the case of two colors—the Black and White Bin Packing problem—we give a lower bound of 2 on the asymptotic competitive ratio of any online algorithm when items have arbitrary size. We also prove that all Any Fit algorithms have the absolute competitive ratio 3. When the items have sizes of at most 1 / d for a real $$d \ge 2$$ we show that the Worst Fit algorithm is absolutely $$(1+d/(d-1))$$-competitive. © Springer Science+Business Media New York 2016 |
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Abstract In the Colored Bin Packing problem a sequence of items of sizes up to 1 arrives to be packed into bins of unit capacity. Each item has one of at least two colors and an additional constraint is that we cannot pack two items of the same color next to each other in the same bin. The objective is to minimize the number of bins. In the important special case when all items have size zero, we characterize the optimal value to be equal to color discrepancy. As our main result, we give an (asymptotically) 1.5-competitive algorithm which is optimal. In fact, the algorithm always uses at most $$\lceil 1.5\cdot OPT \rceil $$ bins and we can force any deterministic online algorithm to use at least $$\lceil 1.5\cdot OPT \rceil $$ bins while the offline optimum is $$ OPT $$ for any value of $$ OPT \ge 2$$. In particular, the absolute competitive ratio of our algorithm is 5 / 3 and this is optimal. For items of arbitrary size we give a lower bound of 2.5 on the asymptotic competitive ratio of any online algorithm and an absolutely 3.5-competitive algorithm. When the items have sizes of at most 1 / d for a real $$d \ge 2$$ the asymptotic competitive ratio of our algorithm is $$1.5+d/(d-1)$$. We also show that classical algorithms First Fit, Best Fit and Worst Fit are not constant competitive, which holds already for three colors and small items. In the case of two colors—the Black and White Bin Packing problem—we give a lower bound of 2 on the asymptotic competitive ratio of any online algorithm when items have arbitrary size. We also prove that all Any Fit algorithms have the absolute competitive ratio 3. When the items have sizes of at most 1 / d for a real $$d \ge 2$$ we show that the Worst Fit algorithm is absolutely $$(1+d/(d-1))$$-competitive. © Springer Science+Business Media New York 2016 |
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