{"title":"On the Dual Gradient Descent Method for the Resource\u0000Allocation Problem in Multiagent Systems","authors":"D. B. Rokhlin","doi":"10.1134/S1990478924020133","DOIUrl":"10.1134/S1990478924020133","url":null,"abstract":"<p> We consider a sequence of block-separable convex programming problems describing the\u0000resource allocation in multiagent systems. We construct several iterative algorithms for setting the\u0000resource prices. Under various assumptions about the utility functions and resource constraints,\u0000we obtain estimates for the average deviation (regret) of the objective function from the optimal\u0000value and the constraint residuals. Here the average is understood as the expectation for\u0000independent identically distributed data and as the time average in the online optimization\u0000problem. The analysis of the problem is carried out by online optimization methods and duality\u0000theory. The algorithms considered use the information concerning the difference between the total\u0000demand and supply that is generated by agents’ reactions to prices and corresponds to the\u0000constraint residuals.\u0000</p>","PeriodicalId":607,"journal":{"name":"Journal of Applied and Industrial Mathematics","volume":"18 2","pages":"316 - 332"},"PeriodicalIF":0.58,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142186795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}