New approaches for solving the block-to-train assignment problem
Railroad planning involves solving two optimization problems: (i) the blocking problem, which determines what blocks to make and how to route traffic over these blocks; and (ii) the train schedule design problem, which determines train origins, destinations, and routes. Once the blocking plan and tr...
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Veröffentlicht in: | Networks 2008-01, Vol.51 (1), p.48-62 |
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description | Railroad planning involves solving two optimization problems: (i) the blocking problem, which determines what blocks to make and how to route traffic over these blocks; and (ii) the train schedule design problem, which determines train origins, destinations, and routes. Once the blocking plan and train schedule have been obtained, the next step is to determine which trains should carry which blocks. This problem, known as the block‐to‐train assignment problem, is considered in this paper. We provide two formulations for this problem: an arc‐based formulation and a path‐based formulation. The latter is generally smaller than the former, and it can better handle practical constraints. We also propose exact and heuristic algorithms based on the path‐based formulation. Our exact algorithm solves an integer programming formulation with CPLEX using both a priori generation and dynamic generation of paths. Our heuristic algorithms include a Lagrangian relaxation‐based method as well as a greedy construction method. We present computational results of our algorithms using the data provided by a major US railroad. We show that we can obtain an optimal solution of the block‐to‐train assignment problem within a few minutes of computational time, and can obtain heuristic solutions with 1–2% deviations from the optimal solutions within a few seconds. © 2007 Wiley Periodicals, Inc. NETWORKS, 2008 |
doi_str_mv | 10.1002/net.20195 |
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Once the blocking plan and train schedule have been obtained, the next step is to determine which trains should carry which blocks. This problem, known as the block‐to‐train assignment problem, is considered in this paper. We provide two formulations for this problem: an arc‐based formulation and a path‐based formulation. The latter is generally smaller than the former, and it can better handle practical constraints. We also propose exact and heuristic algorithms based on the path‐based formulation. Our exact algorithm solves an integer programming formulation with CPLEX using both a priori generation and dynamic generation of paths. Our heuristic algorithms include a Lagrangian relaxation‐based method as well as a greedy construction method. We present computational results of our algorithms using the data provided by a major US railroad. We show that we can obtain an optimal solution of the block‐to‐train assignment problem within a few minutes of computational time, and can obtain heuristic solutions with 1–2% deviations from the optimal solutions within a few seconds. © 2007 Wiley Periodicals, Inc. NETWORKS, 2008</description><identifier>ISSN: 0028-3045</identifier><identifier>EISSN: 1097-0037</identifier><identifier>DOI: 10.1002/net.20195</identifier><identifier>CODEN: NTWKAA</identifier><language>eng</language><publisher>Hoboken: Wiley Subscription Services, Inc., A Wiley Company</publisher><subject>Applied sciences ; assignment problems ; combinatorial optimization ; Computer science; control theory; systems ; Computer systems and distributed systems. User interface ; Exact sciences and technology ; Flows in networks. Combinatorial problems ; heuristics ; Lagrangian relaxation ; Mathematical programming ; mixed integer programming ; Operational research and scientific management ; Operational research. 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Once the blocking plan and train schedule have been obtained, the next step is to determine which trains should carry which blocks. This problem, known as the block‐to‐train assignment problem, is considered in this paper. We provide two formulations for this problem: an arc‐based formulation and a path‐based formulation. The latter is generally smaller than the former, and it can better handle practical constraints. We also propose exact and heuristic algorithms based on the path‐based formulation. Our exact algorithm solves an integer programming formulation with CPLEX using both a priori generation and dynamic generation of paths. Our heuristic algorithms include a Lagrangian relaxation‐based method as well as a greedy construction method. We present computational results of our algorithms using the data provided by a major US railroad. We show that we can obtain an optimal solution of the block‐to‐train assignment problem within a few minutes of computational time, and can obtain heuristic solutions with 1–2% deviations from the optimal solutions within a few seconds. © 2007 Wiley Periodicals, Inc. NETWORKS, 2008</description><subject>Applied sciences</subject><subject>assignment problems</subject><subject>combinatorial optimization</subject><subject>Computer science; control theory; systems</subject><subject>Computer systems and distributed systems. User interface</subject><subject>Exact sciences and technology</subject><subject>Flows in networks. Combinatorial problems</subject><subject>heuristics</subject><subject>Lagrangian relaxation</subject><subject>Mathematical programming</subject><subject>mixed integer programming</subject><subject>Operational research and scientific management</subject><subject>Operational research. Management science</subject><subject>railroad scheduling</subject><subject>shortest path</subject><subject>Software</subject><subject>transportation</subject><issn>0028-3045</issn><issn>1097-0037</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><recordid>eNp1jz1PwzAQhi0EEqUw8A-yMDCktWM7djZQVQpSFYRUYLQurt2GpklkRy399xjCx8R00t3zvqcHoUuCRwTjZFybbpRgkvEjNCA4EzHGVByjQbjJmGLGT9GZ928YE8KJHKCb3OwjaFvXgF4bH9nGRb6pdmW9irq1iYqq0Zu4a-LOQVlH4H25qrem7qIQKSqzPUcnFipvLr7nED3fTReT-3j-OHuY3M5jTang4XWRCSlFCqxImckslZwnliwpgNCWGs0kI5IlSaKJEUtpgS512BpGOQdMh-i679Wu8d4Zq1pXbsEdFMHqU10FdfWlHtirnm3Ba6isg1qX_i-QZTgVPA3cuOf2ZWUO_xeqfLr4aY77ROk78_6bALdRqQie6jWfqTx5kfKJEZXSD0z5doA</recordid><startdate>200801</startdate><enddate>200801</enddate><creator>Jha, Krishna C.</creator><creator>Ahuja, Ravindra K.</creator><creator>Şahin, Güvenç</creator><general>Wiley Subscription Services, Inc., A Wiley Company</general><general>John Wiley & Sons</general><scope>BSCLL</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>200801</creationdate><title>New approaches for solving the block-to-train assignment problem</title><author>Jha, Krishna C. ; Ahuja, Ravindra K. ; Şahin, Güvenç</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3375-30b978876a4b64e9f38552f1d3aa7cf3ec484184222c1e7d8fa3dcec4e4355a03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Applied sciences</topic><topic>assignment problems</topic><topic>combinatorial optimization</topic><topic>Computer science; control theory; systems</topic><topic>Computer systems and distributed systems. User interface</topic><topic>Exact sciences and technology</topic><topic>Flows in networks. Combinatorial problems</topic><topic>heuristics</topic><topic>Lagrangian relaxation</topic><topic>Mathematical programming</topic><topic>mixed integer programming</topic><topic>Operational research and scientific management</topic><topic>Operational research. Management science</topic><topic>railroad scheduling</topic><topic>shortest path</topic><topic>Software</topic><topic>transportation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jha, Krishna C.</creatorcontrib><creatorcontrib>Ahuja, Ravindra K.</creatorcontrib><creatorcontrib>Şahin, Güvenç</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><jtitle>Networks</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jha, Krishna C.</au><au>Ahuja, Ravindra K.</au><au>Şahin, Güvenç</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>New approaches for solving the block-to-train assignment problem</atitle><jtitle>Networks</jtitle><addtitle>Networks</addtitle><date>2008-01</date><risdate>2008</risdate><volume>51</volume><issue>1</issue><spage>48</spage><epage>62</epage><pages>48-62</pages><issn>0028-3045</issn><eissn>1097-0037</eissn><coden>NTWKAA</coden><abstract>Railroad planning involves solving two optimization problems: (i) the blocking problem, which determines what blocks to make and how to route traffic over these blocks; and (ii) the train schedule design problem, which determines train origins, destinations, and routes. Once the blocking plan and train schedule have been obtained, the next step is to determine which trains should carry which blocks. This problem, known as the block‐to‐train assignment problem, is considered in this paper. We provide two formulations for this problem: an arc‐based formulation and a path‐based formulation. The latter is generally smaller than the former, and it can better handle practical constraints. We also propose exact and heuristic algorithms based on the path‐based formulation. Our exact algorithm solves an integer programming formulation with CPLEX using both a priori generation and dynamic generation of paths. Our heuristic algorithms include a Lagrangian relaxation‐based method as well as a greedy construction method. We present computational results of our algorithms using the data provided by a major US railroad. We show that we can obtain an optimal solution of the block‐to‐train assignment problem within a few minutes of computational time, and can obtain heuristic solutions with 1–2% deviations from the optimal solutions within a few seconds. © 2007 Wiley Periodicals, Inc. NETWORKS, 2008</abstract><cop>Hoboken</cop><pub>Wiley Subscription Services, Inc., A Wiley Company</pub><doi>10.1002/net.20195</doi><tpages>15</tpages></addata></record> |
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subjects | Applied sciences assignment problems combinatorial optimization Computer science control theory systems Computer systems and distributed systems. User interface Exact sciences and technology Flows in networks. Combinatorial problems heuristics Lagrangian relaxation Mathematical programming mixed integer programming Operational research and scientific management Operational research. Management science railroad scheduling shortest path Software transportation |
title | New approaches for solving the block-to-train assignment problem |
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