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Link to original content: https://api.crossref.org/works/10.1142/S0217595915500189
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We formulate the problem as a nonlinear program where unit costs charged by agents are described as nonlinear functions. The special case with piecewise constant unit costs is formulated as a mixed integer program. We then develop a two-echelon heuristic algorithm to solve the nonlinear program. The upper echelon of the heuristic assigns shipments to suitable agents by adopting a set of neighborhood policies, while the lower echelon improves the routing plan by consolidating jobs along (sub) paths. The feasibility and validity of the heuristic are examined based on randomly generated instances. Computational results show that the heuristic is able to obtain good solutions in manageable computation time. The effects of network density and iteration limits on the performance of the heuristic are also characterized. <\/jats:p>","DOI":"10.1142\/s0217595915500189","type":"journal-article","created":{"date-parts":[[2015,1,19]],"date-time":"2015-01-19T04:44:00Z","timestamp":1421642640000},"page":"1550018","source":"Crossref","is-referenced-by-count":1,"title":["A Two-Echelon Neighborhood Search Algorithm for a Forwarder's Job Assignment in a Multi-Agent Logistics Network"],"prefix":"10.1142","volume":"32","author":[{"given":"Yong","family":"Wang","sequence":"first","affiliation":[{"name":"College of Economics and Business Administration, Chongqing University, Chongqing 400030, P. R. China"}]},{"given":"Wen","family":"He","sequence":"additional","affiliation":[{"name":"School of Business Administration, Hunan University, Changsha 410082, P. R. 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