{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":1,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":27,"n_cols":5,"rows_kept":27,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[3,2,3,3],[4,2,4,3],[5,2,5,3],[6,2,6,3],[7,2,7,3],[8,2,8,3],[20,2,20,3],[21,2,21,3],[23,2,23,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNINA9910370253803321"]
[null,null,"Titolo",null,"Advances in Optimization and Decision Science for Society, Services and Enterprises : ODS, Genoa, Italy, September 4-7, 2019 / / edited by Massimo Paolucci, Anna Sciomachen, Pierpaolo Uberti"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019"]
[null,null,"ISBN",null,"3-030-34960-8"]
[null,null,"Edizione",null,"[1st ed. 2019.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XI, 503 p. 77 illus., 49 illus. in color.)"]
[null,null,"Collana",null,"AIRO Springer Series, , 2523-7055 ; ; 3"]
[null,null,"Disciplina",null,"519.3"]
[null,null,"Soggetti",null,"Operations research"]
[{"$nulls":4},"Management science"]
[{"$nulls":4},"Mathematical optimization"]
[{"$nulls":4},"Calculus of variations"]
[{"$nulls":4},"Graph theory"]
[{"$nulls":4},"Game theory"]
[{"$nulls":4},"Computer science - Mathematics"]
[{"$nulls":4},"Operations Research, Management Science"]
[{"$nulls":4},"Calculus of Variations and Optimization"]
[{"$nulls":4},"Graph Theory"]
[{"$nulls":4},"Game Theory"]
[{"$nulls":4},"Mathematical Applications in Computer Science"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"1 C. Cervellera et al., A receding horizon approach for berth allocation based on random search optimization -- 2 G. Di Tollo et al., Integrating ship movement scheduling and tug assignment within a canal harbor -- 3 G. Auricchio et al., The Maximum Nearby Flow Problem -- 4 T. Alves de Queiroz et al., Linear models for portfolio selection with real features -- 5 M. Maggi and P. Uberti, Portfolio Leverage in Asset Allocation Problems -- 6 V. Cacchiani et al., Energy-Efficient Train Control -- 7 C. Cervellera and D. Macciò, Gradient boosting with extreme learning machines for the optimization of nonlinear functionals -- 8 M. Benini et al., A MILP model for biological sample transportation in healthcare -- 9 E. Marcelli and R. De Leone, Infinite Kernel Extreme Learning Machine -- 10 A. Betti and M. Gori, "]
[{"$nulls":4},"Least Action Principles and Well-Posed Learning Problems -- 11 M. Casazza and A. Ceselli, Heuristic data-driven feasibility on Integrated Planning and Scheduling -- 12 M. Barbato et al., Evaluatingautomated storage and retrieval system policies with simulation and optimization -- 13 E. Tresoldi and A. Ceselli, Rolling-horizon heuristics for capacitated stochastic inventory problems with forecast updates -- 14 M. Barbato et al., Paths and matchings in an automated warehouse -- 15 H. Aldossary and G. Coates, Coordinating the Emergency Response of Ambulances to Multiple Mass Casualty Incidents using an Optimization-based Approach -- 16 L. Scrimali and G. Fargetta, A game theory model of online content competition -- 17 G. Cappello and P. Daniele, A Variational Formulation for a Human Migration Problem -- 18 M. Cerulli et al., Flying safely by bilevel programming -- 19 S. Basso and A. Ceselli, Computational evaluation of data driven local search for MIP decompositions -- 20 G. Colajanni, An integer programming formulation for University Course Timetabling -- 21 P. Hosein et al., On the Sizing of Security Personnel Staff while accounting for Overtime Pay -- 22 M.‐S. Vié and N. Zufferey, Dynamic Tabu Search for Enhancing the Productivity of a Bottle Production Line -- 23 M. Boccia et al., Swap minimization in nearest neighbour quantum circuits: an ILP formulation -- 24 M. Passacantando and F. Raciti, A traffic equilibrium nonlinear programming model for optimizing road maintenance investments -- 25 L. Mastroeni et al., Opinion dynamics in multi-agent systems under proportional updating and any-to-any influence -- 26 M. F. Monaco and M. Sammarra, A new formulation of the single door truck scheduling problem -- 27 L. Rarità, Optimization of car traffic in emergency conditions -- 28 M. E. Bruni at al., The Cumulative Capacitated Vehicle Routing Problem with Profits under Uncertainty -- 29 P. Beraldi et al., Dealing with the stochastic home energy management problem -- 30 J.-F. Côté et al., Optimization Methods for the Same-Day Delivery Problem -- 31 D. Ambrosino and V. Asta, Intermodality and rail transport: focus on port rail shunting operations -- 32 D. Ferone et al., The k-Color Shortest Path Problem -- 33 M. E. Bruni et al., The Traveling Repairman Problem App for Mobile Phones: a Case on Perishable Product Delivery -- 34 R. Tison and N. Zufferey, Integrating Vehicle Routing and Resource Allocation in a Pharmaceutical Network -- 35 E. Parra, A real case on making strategic logistics decisions with production and inventory optimization models -- 36 A. Alves da Silva Mundim et al., A Bi-objective Mixed Integer Model for the Single Link Inventory Routing Problem Using the e-constraint Method -- 37 M. Pour-Massahian-Tafti et al., Models for Disassembly Lot Sizing Problem with Decisions on Surplus Inventory -- 38 R. Berruto et al., Learning inventory control rules for perishable items by simulation-based optimization -- 39 C. Cerrone et al., A Genetic Algorithm for Minimum Conflict Weighted Spanning Tree Problem -- 40 G. Lancia and M. Dalpasso, Algorithmic strategies for a fast exploration of the TSP 4-OPT neighborhood -- 41 M. Barbato et al., A computational evaluation of online ATSP algorithms -- 42 F. Wamser et al., Modeling of Traffic Flows in Internet of Things Using Renewal Approximation -- 43 F. Davoli et al., Flow Assignment in Multi-Core Network Processors."]
[null,null,null,"Sommario/riassunto","The contributions included in the volume are drawn from presentations at ODS2019 – International Conference on Optimization and Decision Science, which was the 49th annual meeting of the Italian Operations Research Society (AIRO) held at Genoa, Italy, on 4-7 September 2019. This book presents very recent results in the field of Optimization and Decision Science. While the book is addressed primarily to the Operations Research (OR) community, the interdisciplinary contents "]
[{"$nulls":4},"ensure that it will also be of very high interest for scholars and researchers from many scientific disciplines, including computer sciences, economics, mathematics, and engineering. Operations Research is known as the discipline of optimization applied to real-world problems and to complex decision-making fields. The focus is on mathematical and quantitative methods aimed at determining optimal or near-optimal solutions in acceptable computation times. This volume not only presents theoretical results but also coversreal industrial applications, making it interesting for practitioners facing decision problems in logistics, manufacturing production, and services. Readers will accordingly find innovative ideas from both a methodological and an applied perspective."]