Didattica

Mathematical Optimisation


Modalità d'esame

  1. L'esame può essere preparato singolarmente o da un gruppo composto al massimo da due persone.
  2. L'esame consiste di tre parti
    1. Scelta di un articolo (paper) su cui realizzare il progetto.
      1. Il paper deve essere stato pubblicato non prima dell'anno 2020 in uno dei seguenti journals:
      2. Il paper deve trattare un problema per cui è proposto un modello di programmazione lineare (mista-) intera.
      3. Salvo indicazioni contrarie del docente, tutte le tecniche proposte nel paper, anche eventuali euristiche, devono essere incluse nel progetto.
      4. Il paper è a scelta dello studente/gruppo previa conferma da parte del docente, che potrà fornire indicazioni ulteriori sull'esecuzione del lavoro.
    2. Implementazione di un modello (o di una serie di modelli) di programmazione lineare (mista-) intera.
      1. Il linguaggio di programmazione da utilizzare è python. Come solver si deve utilizzare Gurobi.
      2. Il codice consegnato deve contenere
        1. un file test.py in cui vengono eseguiti tutti gli algoritmi proposti (modello + eventuali euristiche) su istanze piccole;
        2. un file scalability.py che deve essere quello utilizzato per l'analisi di scalabilità degli algoritmi.
    3. Una volta inviato il codice al docente via mail, lo studente/gruppo deve preparare una presentazione con slides del lavoro svolto la cui durata deve essere al massimo di 35 minuti.
      1. La presentazione verrà effettuata in presenza in una data da concordarsi con il docente.
      2. L'esposizione della presentazione deve coinvolgere tutti i membri del gruppo in maniera equa.
  3. Non c'è limite di tempo da quando si riceve l'approvazione del paper scelto a quando si invia la mail con l'implementazione.
  4. Nel caso (frequente) in cui dal paper non sia possibile ricavare i dati di input del modello implementato, sarà cura dello studente/gruppo creare un dataset opportuno.
  5. Sarà valutata l'analisi della scalabilità del modello implementato, cioè come si comporta da un punto di vista computazionale il modello all'aumentare delle dimensioni dell'istanza.
  6. Saranno valutati eventuali migliorie e/o estensioni del modello presente nel paper scelto.
  7. All'esposizione seguiranno domande del docente inerenti o legate al progetto.
  8. Non è possibile scegliere un paper che sia stato già assegnato (vedi di seguito).

Papers già assegnati

  1. Al-Shihabi, S., & AlDurgam, M. M. (2020). The contractor time–cost–credit trade-off problem: integer programming model, heuristic solution, and business insights. International Transactions in Operational Research, 27(6), 2841-2877.
  2. Hochbaum, D. S., Rao, X., & Sauppe, J. (2022). Network flow methods for the minimum covariate imbalance problem. European Journal of Operational Research, 300(3), 827-836.
  3. Zhang, S., Hua, L., & Yu, B. (2022). Peak-easing strategies for urban subway operations in the context of COVID-19 epidemic. Transportation Research Part E: Logistics and Transportation Review, 102724.
  4. Hughes, M. S., Lunday, B. J., Weir, J. D., & Hopkinson, K. M. (2021). The multiple shortest path problem with path deconfliction. European Journal of Operational Research, 292(3), 818-829.
  5. Brekkå, I., Randøy, S., Fagerholt, K., Thun, K., & Vadseth, S. T. (2022). The Fish Feed Production Routing Problem. Computers & Operations Research, 144, 105806.
  6. Fontaine, P. (2022). The vehicle routing problem with load-dependent travel times for cargo bicycles. European Journal of Operational Research, 300(3), 1005-1016.
  7. Ramos, N., de Rezende, P. J., & de Souza, C. C. (2022). Optimal area polygonization problems: Exact solutions through geometric duality. Computers & Operations Research, 105842.
  8. Xie, L., Thieme, N., Krenzler, R., & Li, H. (2021). Introducing split orders and optimizing operational policies in robotic mobile fulfillment systems. European Journal of Operational Research, 288(1), 80-97.
  9. Kabadurmus, O., Kazançoglu, Y., Yüksel, D., & Pala, M. Ö. (2022). A circular food supply chain network model to reduce food waste. Annals of Operations Research, 1-31.
  10. Jamili, N., van den Berg, P. L., & de Koster, R. (2022). Quantifying the impact of sharing resources in a collaborative warehouse. European Journal of Operational Research, 302(2), 518-519.
  11. Xu, C., Chang, W., & Liu, W. (2022). Data-driven decision model based on local two-stage weighted ensemble learning. Annals of Operations Research, 1-34.
  12. dos Santos, A. G., Viana, A., & Pedroso, J. P. (2022). 2-echelon lastmile delivery with lockers and occasional couriers. Transportation Research Part E: Logistics and Transportation Review, 162, 102714.
  13. Li, X., Huang, Y. H., Fang, S. C., & Zhang, Y. (2020). An alternative efficient representation for the project portfolio selection problem. European Journal of Operational Research, 281(1), 100-113.
  14. Pottel, S., & Goel, A. (2022). Scheduling activities with time-dependent durations and resource consumptions. European Journal of Operational Research, 301(2), 445-457.
  15. Sun, Y., Wang, S., Shen, Y., Li, X., Ernst, A. T., & Kirley, M. (2022). Boosting ant colony optimization via solution prediction and machine learning. Computers & Operations Research, 143, 105769.
  16. Mancini, S., Triki, C., & Piya, S. (2022). Optimal selection of touristic packages based on user preferences during sports mega-events. European Journal of Operational Research, 302(3), 819-830.
  17. Pina-Pardo, J. C., Silva, D. F., & Smith, A. E. (2021). The traveling salesman problem with release dates and drone resupply. Computers & Operations Research, 129, 105170.
  18. Gandra, V. S., Çalik, H., Toffolo, T. A., Carvalho, M. A. M., & Berghe, G. V. (2022). The vessel swap-body routing problem. European Journal of Operational Research, 303(1), 354-369.
  19. Alonso, M. T., Martinez-Sykora, A., Alvarez-Valdes, R., & Parreño, F. (2022). The pallet-loading vehicle routing problem with stability constraints. European Journal of Operational Research, 302(3), 860-873.
  20. Bhaya, A., & Kaszkurewicz, E. (2022). The generalized cash balance problem: optimization-based one step ahead optimal control. International Transactions in Operational Research.
  21. Alozie, G. U., Arulselvan, A., Akartunal?, K., & Pasiliao Jr, E. L. (2021). Efficient methods for the distance-based critical node detection problem in complex networks. Computers & Operations Research, 131, 105254.
  22. Luo, Y., Golden, B., Poikonen, S., Wasil, E., & Zhang, R. (2023). The paired mail carrier problem. European Journal of Operational Research, 308(2), 801-817.
  23. Salama, M. R., & Srinivas, S. (2022). Collaborative truck multi-drone routing and scheduling problem: Package delivery with flexible launch and recovery sites. Transportation Research Part E: Logistics and Transportation Review, 164, 102788.
  24. Poikonen, S., & Golden, B. (2020). Multi-visit drone routing problem. Computers & Operations Research, 113, 104802.
  25. Bacci, T., Mattia, S., & Ventura, P. (2020). A branch-and-cut algorithm for the restricted block relocation problem. European Journal of Operational Research, 287(2), 452-459.
  26. Silva, A., Coelho, L. C., Darvish, M., & Renaud, J. (2022). A cutting plane method and a parallel algorithm for packing rectangles in a circular container. European Journal of Operational Research, 303(1), 114-128.
  27. Zheng, J., Hong, Y., Xu, W., Li, W., & Chen, Y. (2022). An effective iterated two-stage heuristic algorithm for the multiple Traveling Salesmen Problem. Computers & Operations Research, 143, 105772.
  28. Salehipour, A. (2022). An Optimization Method for Characterizing Two Groups of Data. International Transactions in Operational Research.
  29. Ahmadian, M. M., & Salehipour, A. (2022). Heuristics for flights arrival scheduling at airports. International Transactions in Operational Research, 29(4), 2316-2345.
  30. Akhlaghi, V. E., & Campbell, A. M. (2022). The two-echelon island fuel distribution problem. European Journal of Operational Research, 302(3), 999-1017.
  31. Tönissen, D. D., & Schlicher, L. (2021). Using 3D-printing in disaster response: The two-stage stochastic 3D-printing knapsack problem. Computers & Operations Research, 133, 105356.
  32. Mancini, S., Gansterer, M., & Hartl, R. F. (2021). The collaborative consistent vehicle routing problem with workload balance. European Journal of Operational Research, 293(3), 955-965.
  33. Krutein, K. F., & Goodchild, A. (2022). The isolated community evacuation problem with mixed integer programming. Transportation Research Part E: Logistics and Transportation Review, 161, 102710.
  34. Che, Y., Hu, K., Zhang, Z., & Lim, A. (2021). Machine scheduling with orientation selection and two-dimensional packing for additive manufacturing. Computers & Operations Research, 130, 105245.
  35. Xu, M., Yan, X., & Yin, Y. (2022). Truck routing and platooning optimization considering drivers’ mandatory breaks. Transportation Research Part C: Emerging Technologies, 143, 103809.
  36. Demeulemeester, T., Goossens, D., Hermans, B., & Leus, R. (2023). A pessimist’s approach to one-sided matching. European Journal of Operational Research, 305(3), 1087-1099.
  37. Karsu, Ö., & Solyalı, O. (2023). A new formulation and an effective matheuristic for the airport gate assignment problem. Computers & Operations Research, 151, 106073.
  38. Morgenroth, C., Boysen, N., Schwerdfeger, S., & Weidinger, F. (2021). Scheduling taxi services for a team of car relocators. Computers & Operations Research, 128, 105188.
  39. Kyriakakis, N. A., Marinaki, M., Matsatsinis, N., & Marinakis, Y. (2022). A cumulative unmanned aerial vehicle routing problem approach for humanitarian coverage path planning. European Journal of Operational Research, 300(3), 992-1004.
  40. Bazirha, M., Kadrani, A., & Benmansour, R. (2023). Stochastic home health care routing and scheduling problem with multiple synchronized services. Annals of Operations Research, 320(2), 573-601.
  41. Zhang, Y., Lin, W. H., Huang, M., & Hu, X. (2021). Multi-warehouse package consolidation for split orders in online retailing. European Journal of Operational Research, 289(3), 1040-1055.
  42. Luo, Y., Golden, B., Poikonen, S., & Zhang, R. (2022). A fresh look at the Traveling Salesman Problem with a Center. Computers & Operations Research, 143, 105748.
  43. Witteman, M., Deng, Q., & Santos, B. F. (2021). A bin packing approach to solve the aircraft maintenance task allocation problem. European Journal of Operational Research, 294(1), 365-376.
  44. Xu, Y., Wandelt, S., & Sun, X. (2021). Airline integrated robust scheduling with a variable neighborhood search based heuristic. Transportation Research Part B: Methodological, 149, 181-203.
  45. Dell'Amico, M., Montemanni, R., & Novellani, S. (2023) Pickup and Delivery with Lockers. Transportation Research Part C: Emerging Technologies, 148, 104022.
  46. Kurowski, K., Pecyna, T., Slysz, M., Różycki, R., Waligóra, G., & Węglarz, J. (2023). Application of quantum approximate optimization algorithm to job shop scheduling problem. European Journal of Operational Research, 310(2), 518-528.
  47. Yin, J., D’Ariano, A., Wang, Y., Yang, L., & Tang, T. (2021). Timetable coordination in a rail transit network with time-dependent passenger demand. European Journal of Operational Research, 295(1), 183-202.
  48. Baller, R., Fontaine, P., Minner, S., & Lai, Z. (2022). Optimizing automotive inbound logistics: A mixed-integer linear programming approach. Transportation Research Part E: Logistics and Transportation Review, 163, 102734.
  49. Liu, Q., Lin, X., Li, M., Li, L., & He, F. (2023). Coordinated lane-changing scheduling of multilane CAV platoons in heterogeneous scenarios. Transportation Research Part C: Emerging Technologies, 147, 103992.
  50. Shiri, D., Akbari, V., & Tozan, H. (2023). Online optimisation for ambulance routing in disaster response with partial or no information on victim conditions. Computers & Operations Research, 106314.
  51. Monaci, M., Pike-Burke, C., & Santini, A. (2022). Exact algorithms for the 0–1 Time-bomb Knapsack Problem. Computers & Operations Research, 145, 105848.
  52. De, A., Gorton, M., Hubbard, C., & Aditjandra, P. (2022). Optimization model for sustainable food supply chains: An application to Norwegian salmon. Transportation Research Part E: Logistics and Transportation Review, 161, 102723.
  53. Araújo, E. J., Darvish, M., & Renaud, J. (2023). The road train optimization problem with load assignment. Computers & Operations Research, 153, 106184.
  54. Mendes, A. B., & e Alvelos, F. P. (2023). Iterated local search for the placement of wildland fire suppression resources. European Journal of Operational Research, 304(3), 887-900.
  55. Cazzaro, D., Koza, D. F., & Pisinger, D. (2023). Combined layout and cable optimization of offshore wind farms. European Journal of Operational Research, 311(1), 301-315.
  56. Dong, Z. L., Ribeiro, C. C., Xu, F., Zamora, A., Ma, Y., & Jing, K. (2023). Dynamic scheduling of e-sports tournaments. Transportation Research Part E: Logistics and Transportation Review, 169, 102988.
  57. Olmez, O. B., Gultekin, C., Balcik, B., Ekici, A., & Özener, O. Ö. (2022). A variable neighborhood search based matheuristic for a waste cooking oil collection network design problem. European Journal of Operational Research, 302(1), 187-202.
  58. Zhang, H., Yao, S., Liu, Q., Leng, J., & Wei, L. (2023). Exact approaches for the unconstrained two-dimensional cutting problem with defects. Computers & Operations Research, 106407.
  59. Kloster, K., Moeini, M., Vigo, D., & Wendt, O. (2023). The multiple traveling salesman problem in presence of drone-and robot-supported packet stations. European Journal of Operational Research, 305(2), 630-643.
  60. Biró, P., & Gyetvai, M. (2023). Online voluntary mentoring: Optimising the assignment of students and mentors. European Journal of Operational Research, 307(1), 392-405.
  61. Tran, T. H., Nguyen, T. B. T., Le, H. S. T., & Phung, D. C. (2024). Formulation and solution technique for agricultural waste collection and transport network design. European Journal of Operational Research, 313(3), 1152-1169.
  62. Caselli, G., Delorme, M., Iori, M., & Magni, C. A. (2024). Exact algorithms for a parallel machine scheduling problem with workforce and contiguity constraints. Computers & Operations Research, 163, 106484.
  63. Lyu, Z., & Yu, A. J. (2023). The pickup and delivery problem with transshipments: Critical review of two existing models and a new formulation. European Journal of Operational Research, 305(1), 260-270.
  64. Bigler, T., Kammermann, M., & Baumann, P. (2023). A matheuristic for a customer assignment problem in direct marketing. European Journal of Operational Research, 304(2), 689-708.
  65. Fonseca, G. H., Figueiroa, G. B., & Toffolo, T. A. (2024). A fix-and-optimize heuristic for the Unrelated Parallel Machine Scheduling Problem. Computers & Operations Research, 163, 106504.
  66. Morais, R., Bulhões, T., & Subramanian, A. (2024). Exact and heuristic algorithms for minimizing the makespan on a single machine scheduling problem with sequence-dependent setup times and release dates. European Journal of Operational Research, 315(2), 442-453.
  67. Nguyen, M. A., Dang, G. T. H., Hà, M. H., & Pham, M. T. (2022). The min-cost parallel drone scheduling vehicle routing problem. European Journal of Operational Research, 299(3), 910-930.
  68. Weidinger, F., Albiński, S., & Boysen, N. (2023). Matching supply and demand for free-floating car sharing: On the value of optimization. European Journal of Operational Research, 308(3), 1380-1395.
  69. Faria, A. F., de Souza, S. R., & de Sa, E. M. (2021). A mixed-integer linear programming model to solve the Multidimensional Multi-Way Number Partitioning Problem. Computers & Operations Research, 127, 105133.
  70. Ferone, D., Festa, P., & Guerriero, F. (2022). The rainbow steiner tree problem. Computers & Operations Research, 139, 105621.
  71. Weiner, J., Ernst, A. T., Li, X., Sun, Y., & Deb, K. (2021). Solving the maximum edge disjoint path problem using a modified Lagrangian particle swarm optimisation hybrid. European Journal of Operational Research, 293(3), 847-862.
  72. Myung, Y. S., & Yu, Y. M. (2020). Freight transportation network model with bundling option. Transportation Research Part E: Logistics and Transportation Review, 133, 101827.
  73. Campêlo, M., & Figueiredo, T. F. (2021). Integer programming approaches to the multiple team formation problem. Computers & Operations Research, 133, 105354.
  74. Terán-Viadero, P., Alonso-Ayuso, A., & Martín-Campo, F. J. (2024). Mathematical optimisation in the honeycomb cardboard industry: A model for the two-dimensional variable-sized cutting stock problem. European Journal of Operational Research, 319(1), 303-315.
  75. Klein, N., Gnägi, M., & Trautmann, N. (2024). Mixed-integer linear programming for project scheduling under various resource constraints. European Journal of Operational Research, 319(1), 79-88.
  76. Hill, A., & Peuker, S. (2024). Expanding students’ social networks via optimized team assignments. Annals of Operations Research, 332(1), 1107-1131.
  77. Lunday, B. J. (2024). The maximal covering location disruption problem. Computers & Operations Research, 169, 106721.
  78. Cohen, I. R., Cohen, I., & Zaks, I. (2023). A theoretical and empirical study of job scheduling in cloud computing environments: the weighted completion time minimization problem with capacitated parallel machines. Annals of Operations Research, 1-24.
  79. Tirkolaee, E. B., Goli, A., Gütmen, S., Weber, G. W., & Szwedzka, K. (2023). A novel model for sustainable waste collection arc routing problem: Pareto-based algorithms. Annals of Operations Research, 324(1), 189-214.
  80. Grus, J., & Hanzálek, Z. (2024). Automated placement of analog integrated circuits using priority-based constructive heuristic. Computers & Operations Research, 167, 106643.
  81. Pan, X., & Guo, S. (2023). Dual-objective optimization of a green closed-loop supply chain in steel industry considering quantity discount. Annals of Operations Research, 1-27.
  82. Cui, S., Gao, K., Yu, B., Ma, Z., & Najafi, A. (2023). Joint optimal vehicle and recharging scheduling for mixed bus fleets under limited chargers. Transportation Research Part E: Logistics and Transportation Review, 180, 103335.
  83. Zhu, W., Hu, X., Pei, J., & Pardalos, P. M. (2024). Minimizing the total travel distance for the locker-based drone delivery: A branch-and-cut-based method. Transportation Research Part B: Methodological, 184, 102950.
  84. Sun, Z., Benlic, U., Li, M., & Wu, Q. (2022). Reinforcement learning based tabu search for the minimum load coloring problem. Computers & Operations Research, 143, 105745.
  85. Senna, F., Coelho, L. C., Morabito, R., & Munari, P. (2024). An exact method for a last-mile delivery routing problem with multiple deliverymen. European Journal of Operational Research, 317(2), 550-562.
  86. Tamke, F., & Buscher, U. (2023). The vehicle routing problem with drones and drone speed selection. Computers & Operations Research, 152, 106112.
  87. Tang, L., D’Ariano, A., Xu, X., Li, Y., Ding, X., & Samà, M. (2021). Scheduling local and express trains in suburban rail transit lines: Mixed–integer nonlinear programming and adaptive genetic algorithm. Computers & Operations Research, 135, 105436.
  88. Akhundov, N., & Ostrowski, J. (2024). Exploiting symmetry for the job sequencing and tool switching problem. European Journal of Operational Research, 316(3), 976-987.
  89. de Weert, Y. R., Gkiotsalitis, K., & van Berkum, E. C. (2024). Improving the scheduling of railway maintenance projects by minimizing passenger delays subject to event requests of railway operators. Computers & Operations Research, 165, 106580.
  90. Marzo, R. G., Melo, R. A., Ribeiro, C. C., & Santos, M. C. (2022). New formulations and branch-and-cut procedures for the longest induced path problem. Computers & Operations Research, 139, 105627.
  91. Durán, G., Guajardo, M., & Gutiérrez, F. (2022). Efficient referee assignment in Argentinean professional basketball leagues using operations research methods. Annals of Operations Research, 316, 1121-1139.
  92. Arias-Melia, P., Liu, J., & Mandania, R. (2022). The vehicle sharing and task allocation problem: MILP formulation and a heuristic solution approach. Computers & Operations Research, 147, 105929.
  93. Boccia, M., Mancuso, A., Masone, A., & Sterle, C. (2024). Exact and heuristic approaches for the truck–drone team logistics problem. Transportation Research Part C: Emerging Technologies, 165, 104691.
  94. Hao, Y., Chen, Z., Sun, X., & Tong, L. (2025). Planning of truck platooning for road-network capacitated vehicle routing problem. Transportation Research Part E: Logistics and Transportation Review, 194, 103898.
  95. Hyder, J., & Hassini, E. (2025). Optimizing warehouse space allocation to maximize profit in the postal industry. Transportation Research Part E: Logistics and Transportation Review, 195, 103924.
  96. Zaidi, I., Oulamara, A., Idoumghar, L., & Basset, M. (2024). Minimizing grid capacity in preemptive electric vehicle charging orchestration: Complexity, exact and heuristic approaches. European Journal of Operational Research, 312(1), 22-37.
  97. Battaïa, O., Dolgui, A., Guschinsky, N., & Kovalyov, M. Y. (2023). Designing fast-charge urban electric bus services: An Integer Linear Programming model. Transportation Research Part E: Logistics and Transportation Review, 171, 103065.
  98. Cerrone, C., & Russo, D. D. (2023). An exact reduction technique for the k-Colour Shortest Path Problem. Computers & Operations Research, 149, 106027.
  99. Balster, I., Caetano, J. A., Ribeiro, G. M., & Bahiense, L. (2025). Optimizing the Transport of Organs for Transplantation. Computers & Operations Research, 176, 106934.
  100. Cherubini, D., Fanni, A., Mereu, A., Frangioni, A., Murgia, C., Scutellà, M. G., & Zuddas, P. (2011). Linear programming models for traffic engineering in 100% survivable networks under combined IS–IS/OSPF and MPLS-TE. Computers & Operations Research, 38(12), 1805-1815.
  101. Uchida, K., Wang, Y., & Tani, R. (2025). Reliable pathfinding problems for a correlated network: A linear programming problem in a hypergraph. European Journal of Operational Research.
  102. Marshall, S. E., & Mohaghegh, M. (2025). Comparison of a rule-based heuristic and a linear programming model for assigning mentees and mentors in a women in technology mentoring programme. Computers & Operations Research, 107002.
  103. Zhou, Q., Zhu, T., Wu, Q., Jiang, Z. Z., & Wang, W. (2025). An efficient iterated local search for the minimum quasi-clique partitioning problem. Computers & Operations Research, 179, 107033.
  104. Àlvarez-Miranda, E., Goycoolea, M., Ljubić, I., & Sinnl, M. (2021). The generalized reserve set covering problem with connectivity and buffer requirements. European Journal of Operational Research, 289(3), 1013-1029.
  105. Zinder, Y., Berlińska, J., & Lin, B. M. (2024). Scheduling jobs with shared additional operations on parallel identical machines. Computers & Operations Research, 170, 106780.
  106. Montemanni, R., & Smith, D. H. (2025). Model-based algorithms for the 0-1 Time-Bomb Knapsack Problem. Computers & Operations Research, 107010.
  107. Filippi, C., Guastaroba, G., & Speranza, M. G. (2021). On single-source capacitated facility location with cost and fairness objectives. European Journal of Operational Research, 289(3), 959-974.
  108. Taslimi, B., Sarijaloo, F. B., Liu, H., & Pardalos, P. M. (2022). A novel mixed integer programming model for freight train travel time estimation. European Journal of Operational Research, 300(2), 676-688.
  109. Ghoniem, A., Boz, S., & El-Adle, A. M. (2025). Parcel delivery by vehicle and drone in ordered customer neighborhoods. Transportation Research Part E: Logistics and Transportation Review, 197, 104047.
  110. Fontes, D. B., Homayouni, S. M., & Gonçalves, J. F. (2023). A hybrid particle swarm optimization and simulated annealing algorithm for the job shop scheduling problem with transport resources. European Journal of Operational Research, 306(3), 1140-1157.
  111. Tran, C. Q., Keyvan-Ekbatani, M., Ngoduy, D., & Watling, D. (2022). Dynamic wireless charging lanes location model in urban networks considering route choices. Transportation Research Part C: Emerging Technologies, 139, 103652.
  112. Cerulli, R., Guerriero, F., Scalzo, E., & Sorgente, C. (2023). Shortest paths with exclusive-disjunction arc pairs conflicts. Computers & Operations Research, 152, 106158.
  113. Hong, X., Meng, L., D'Ariano, A., Veelenturf, L. P., Long, S., & Corman, F. (2021). Integrated optimization of capacitated train rescheduling and passenger reassignment under disruptions. Transportation Research Part C: Emerging Technologies, 125, 103025.
  114. Ogazón, E., Anaya-Arenas, A. M., & Ruiz, A. (2025). Designing hub-based regional transportation networks with service level constraints. Transportation Research Part E: Logistics and Transportation Review, 195, 103991.
  115. Eskandarzadeh, S., & Fahimnia, B. (2024). Containerised parcel delivery: Modelling and performance evaluation. Transportation Research Part E: Logistics and Transportation Review, 186, 103519.
  116. Yu, C., Sun, W., Liu, H. X., & Yang, X. (2019). Managing connected and automated vehicles at isolated intersections: From reservation-to optimization-based methods. Transportation research part B: methodological, 122, 416-435.
  117. Sun, Y., Chen, Z. L., & Zhang, L. (2020). Nonprofit peer-to-peer ridesharing optimization. Transportation Research Part E: Logistics and Transportation Review, 142, 102053.
  118. Gajda, M., Gallay, O., Mansini, R., & Ranza, F. (2025). Optimizing last-mile delivery through crowdshipping on public transportation networks. Transportation Research Part C: Emerging Technologies, 179, 105250.
  119. Raviv, T. (2023). The service points’ location and capacity problem. Transportation Research Part E: Logistics and Transportation Review, 176, 103216.
  120. Dong, Z., Che, A., & Feng, J. (2025). Mathematical models and heuristics for double-load crane scheduling in slab yards. European Journal of Operational Research, 324(3), 773-786.
  121. Boccia, M., Masone, A., Sterle, C., & Murino, T. (2023). The parallel AGV scheduling problem with battery constraints: A new formulation and a matheuristic approach. European Journal of Operational Research, 307(2), 590-603.
  122. Lera-Romero, G., Bront, J. J. M., & Soulignac, F. J. (2024). A branch-cut-and-price algorithm for the time-dependent electric vehicle routing problem with time windows. European Journal of Operational Research, 312(3), 978-995.
  123. Kinene, A., Birolini, S., Cattaneo, M., & Granberg, T. A. (2023). Electric aircraft charging network design for regional routes: A novel mathematical formulation and kernel search heuristic. European Journal of Operational Research, 309(3), 1300-1315.
  124. Fischer, V., Paneque, M. P., Legrain, A., & Bürgy, R. (2024). A capacitated multi-vehicle covering tour problem on a road network and its application to waste collection. European Journal of Operational Research, 315(1), 338-353.


Informazioni aggiornate al: 08.9.2025 alle ore 16:11