{"title":"Approximate maximin share allocation for indivisible goods under a knapsack constraint","authors":"Bin Deng, Weidong Li","doi":"10.1007/s10878-025-01331-1","DOIUrl":null,"url":null,"abstract":"<p>The maximin share (MMS) allocation problem under a knapsack constraint is to allocate a set of indivisible goods to a set of <i>n</i> heterogeneous agents, such that the total cost of the allocated goods does not exceed the given budget, and the approximation ratio of the MMS allocation is as large as possible. For any <span><span style=\"\"></span><span data-mathml='<math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mi>&#x03F5;</mi><mo>&#x2208;</mo><mo stretchy=\"false\">(</mo><mn>0</mn><mo>,</mo><mn>1</mn><mo stretchy=\"false\">)</mo></math>' role=\"presentation\" style=\"font-size: 100%; display: inline-block; position: relative;\" tabindex=\"0\"><svg aria-hidden=\"true\" focusable=\"false\" height=\"2.614ex\" role=\"img\" style=\"vertical-align: -0.706ex;\" viewbox=\"0 -821.4 3854.7 1125.3\" width=\"8.953ex\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g fill=\"currentColor\" stroke=\"currentColor\" stroke-width=\"0\" transform=\"matrix(1 0 0 -1 0 0)\"><use x=\"0\" xlink:href=\"#MJMATHI-3F5\" y=\"0\"></use><use x=\"684\" xlink:href=\"#MJMAIN-2208\" y=\"0\"></use><use x=\"1629\" xlink:href=\"#MJMAIN-28\" y=\"0\"></use><use x=\"2019\" xlink:href=\"#MJMAIN-30\" y=\"0\"></use><use x=\"2519\" xlink:href=\"#MJMAIN-2C\" y=\"0\"></use><use x=\"2964\" xlink:href=\"#MJMAIN-31\" y=\"0\"></use><use x=\"3465\" xlink:href=\"#MJMAIN-29\" y=\"0\"></use></g></svg><span role=\"presentation\"><math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mi>ϵ</mi><mo>∈</mo><mo stretchy=\"false\">(</mo><mn>0</mn><mo>,</mo><mn>1</mn><mo stretchy=\"false\">)</mo></math></span></span><script type=\"math/tex\">\\epsilon \\in (0, 1)</script></span>, we prove that <span><span style=\"\"></span><span data-mathml='<math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mo stretchy=\"false\">(</mo><mfrac><mn>93</mn><mn>95</mn></mfrac><mo>+</mo><mi>&#x03F5;</mi><mo stretchy=\"false\">)</mo></math>' role=\"presentation\" style=\"font-size: 100%; display: inline-block; position: relative;\" tabindex=\"0\"><svg aria-hidden=\"true\" focusable=\"false\" height=\"3.215ex\" role=\"img\" style=\"vertical-align: -1.006ex;\" viewbox=\"0 -950.8 3476.3 1384.1\" width=\"8.074ex\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g fill=\"currentColor\" stroke=\"currentColor\" stroke-width=\"0\" transform=\"matrix(1 0 0 -1 0 0)\"><use x=\"0\" xlink:href=\"#MJMAIN-28\" y=\"0\"></use><g transform=\"translate(389,0)\"><g transform=\"translate(120,0)\"><rect height=\"60\" stroke=\"none\" width=\"827\" x=\"0\" y=\"220\"></rect><g transform=\"translate(60,407)\"><use transform=\"scale(0.707)\" xlink:href=\"#MJMAIN-39\"></use><use transform=\"scale(0.707)\" x=\"500\" xlink:href=\"#MJMAIN-33\" y=\"0\"></use></g><g transform=\"translate(60,-363)\"><use transform=\"scale(0.707)\" xlink:href=\"#MJMAIN-39\"></use><use transform=\"scale(0.707)\" x=\"500\" xlink:href=\"#MJMAIN-35\" y=\"0\"></use></g></g></g><use x=\"1679\" xlink:href=\"#MJMAIN-2B\" y=\"0\"></use><use x=\"2680\" xlink:href=\"#MJMATHI-3F5\" y=\"0\"></use><use x=\"3086\" xlink:href=\"#MJMAIN-29\" y=\"0\"></use></g></svg><span role=\"presentation\"><math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mo stretchy=\"false\">(</mo><mfrac><mn>93</mn><mn>95</mn></mfrac><mo>+</mo><mi>ϵ</mi><mo stretchy=\"false\">)</mo></math></span></span><script type=\"math/tex\">(\\frac{93}{95}+ \\epsilon )</script></span>-approximate MMS allocation does not always exist for two agents, while the MMS allocation problem without a knapsack constraint always has an MMS allocation for two agents. We propose a bag-filling based algorithm that can produce a <span><span style=\"\"></span><span data-mathml='<math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mfrac><mi>n</mi><mrow><mn>3</mn><mi>n</mi><mo>&#x2212;</mo><mn>2</mn></mrow></mfrac></math>' role=\"presentation\" style=\"font-size: 100%; display: inline-block; position: relative;\" tabindex=\"0\"><svg aria-hidden=\"true\" focusable=\"false\" height=\"2.914ex\" role=\"img\" style=\"vertical-align: -1.106ex;\" viewbox=\"0 -778.3 2042.9 1254.7\" width=\"4.745ex\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g fill=\"currentColor\" stroke=\"currentColor\" stroke-width=\"0\" transform=\"matrix(1 0 0 -1 0 0)\"><g transform=\"translate(120,0)\"><rect height=\"60\" stroke=\"none\" width=\"1802\" x=\"0\" y=\"220\"></rect><use transform=\"scale(0.707)\" x=\"974\" xlink:href=\"#MJMATHI-6E\" y=\"564\"></use><g transform=\"translate(60,-363)\"><use transform=\"scale(0.707)\" x=\"0\" xlink:href=\"#MJMAIN-33\" y=\"0\"></use><use transform=\"scale(0.707)\" x=\"500\" xlink:href=\"#MJMATHI-6E\" y=\"0\"></use><use transform=\"scale(0.707)\" x=\"1101\" xlink:href=\"#MJMAIN-2212\" y=\"0\"></use><use transform=\"scale(0.707)\" x=\"1879\" xlink:href=\"#MJMAIN-32\" y=\"0\"></use></g></g></g></svg><span role=\"presentation\"><math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mfrac><mi>n</mi><mrow><mn>3</mn><mi>n</mi><mo>−</mo><mn>2</mn></mrow></mfrac></math></span></span><script type=\"math/tex\">\\frac{n}{3n-2}</script></span>-approximate MMS allocation. When <span><span style=\"\"></span><span data-mathml='<math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mi>n</mi><mo>=</mo><mn>2</mn></math>' role=\"presentation\" style=\"font-size: 100%; display: inline-block; position: relative;\" tabindex=\"0\"><svg aria-hidden=\"true\" focusable=\"false\" height=\"1.912ex\" role=\"img\" style=\"vertical-align: -0.205ex;\" viewbox=\"0 -735.2 2435.1 823.4\" width=\"5.656ex\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g fill=\"currentColor\" stroke=\"currentColor\" stroke-width=\"0\" transform=\"matrix(1 0 0 -1 0 0)\"><use x=\"0\" xlink:href=\"#MJMATHI-6E\" y=\"0\"></use><use x=\"878\" xlink:href=\"#MJMAIN-3D\" y=\"0\"></use><use x=\"1934\" xlink:href=\"#MJMAIN-32\" y=\"0\"></use></g></svg><span role=\"presentation\"><math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mi>n</mi><mo>=</mo><mn>2</mn></math></span></span><script type=\"math/tex\">n=2</script></span> and <span><span style=\"\"></span><span data-mathml='<math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mi>n</mi><mo>=</mo><mn>3</mn></math>' role=\"presentation\" style=\"font-size: 100%; display: inline-block; position: relative;\" tabindex=\"0\"><svg aria-hidden=\"true\" focusable=\"false\" height=\"1.912ex\" role=\"img\" style=\"vertical-align: -0.205ex;\" viewbox=\"0 -735.2 2435.1 823.4\" width=\"5.656ex\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g fill=\"currentColor\" stroke=\"currentColor\" stroke-width=\"0\" transform=\"matrix(1 0 0 -1 0 0)\"><use x=\"0\" xlink:href=\"#MJMATHI-6E\" y=\"0\"></use><use x=\"878\" xlink:href=\"#MJMAIN-3D\" y=\"0\"></use><use x=\"1934\" xlink:href=\"#MJMAIN-33\" y=\"0\"></use></g></svg><span role=\"presentation\"><math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mi>n</mi><mo>=</mo><mn>3</mn></math></span></span><script type=\"math/tex\">n=3</script></span>, by more careful analysis, we improve the approximation ratios to <span><span style=\"\"></span><span data-mathml='<math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mfrac><mn>2</mn><mn>3</mn></mfrac></math>' role=\"presentation\" style=\"font-size: 100%; display: inline-block; position: relative;\" tabindex=\"0\"><svg aria-hidden=\"true\" focusable=\"false\" height=\"3.209ex\" role=\"img\" style=\"vertical-align: -1.005ex;\" viewbox=\"0 -949.2 713.9 1381.8\" width=\"1.658ex\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g fill=\"currentColor\" stroke=\"currentColor\" stroke-width=\"0\" transform=\"matrix(1 0 0 -1 0 0)\"><g transform=\"translate(120,0)\"><rect height=\"60\" stroke=\"none\" width=\"473\" x=\"0\" y=\"220\"></rect><use transform=\"scale(0.707)\" x=\"84\" xlink:href=\"#MJMAIN-32\" y=\"556\"></use><use transform=\"scale(0.707)\" x=\"84\" xlink:href=\"#MJMAIN-33\" y=\"-512\"></use></g></g></svg><span role=\"presentation\"><math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mfrac><mn>2</mn><mn>3</mn></mfrac></math></span></span><script type=\"math/tex\">\\frac{2}{3}</script></span> and <span><span style=\"\"></span><span data-mathml='<math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mfrac><mn>1</mn><mn>2</mn></mfrac></math>' role=\"presentation\" style=\"font-size: 100%; display: inline-block; position: relative;\" tabindex=\"0\"><svg aria-hidden=\"true\" focusable=\"false\" height=\"3.209ex\" role=\"img\" style=\"vertical-align: -1.005ex;\" viewbox=\"0 -949.2 713.9 1381.8\" width=\"1.658ex\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g fill=\"currentColor\" stroke=\"currentColor\" stroke-width=\"0\" transform=\"matrix(1 0 0 -1 0 0)\"><g transform=\"translate(120,0)\"><rect height=\"60\" stroke=\"none\" width=\"473\" x=\"0\" y=\"220\"></rect><use transform=\"scale(0.707)\" x=\"84\" xlink:href=\"#MJMAIN-31\" y=\"556\"></use><use transform=\"scale(0.707)\" x=\"84\" xlink:href=\"#MJMAIN-32\" y=\"-513\"></use></g></g></svg><span role=\"presentation\"><math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mfrac><mn>1</mn><mn>2</mn></mfrac></math></span></span><script type=\"math/tex\">\\frac{1}{2}</script></span>, respectively.</p>","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"50 1","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Combinatorial Optimization","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s10878-025-01331-1","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
The maximin share (MMS) allocation problem under a knapsack constraint is to allocate a set of indivisible goods to a set of n heterogeneous agents, such that the total cost of the allocated goods does not exceed the given budget, and the approximation ratio of the MMS allocation is as large as possible. For any , we prove that -approximate MMS allocation does not always exist for two agents, while the MMS allocation problem without a knapsack constraint always has an MMS allocation for two agents. We propose a bag-filling based algorithm that can produce a -approximate MMS allocation. When and , by more careful analysis, we improve the approximation ratios to and , respectively.
期刊介绍:
The objective of Journal of Combinatorial Optimization is to advance and promote the theory and applications of combinatorial optimization, which is an area of research at the intersection of applied mathematics, computer science, and operations research and which overlaps with many other areas such as computation complexity, computational biology, VLSI design, communication networks, and management science. It includes complexity analysis and algorithm design for combinatorial optimization problems, numerical experiments and problem discovery with applications in science and engineering.
The Journal of Combinatorial Optimization publishes refereed papers dealing with all theoretical, computational and applied aspects of combinatorial optimization. It also publishes reviews of appropriate books and special issues of journals.