Teknisyen Rotalama ve Çizelgeleme Probleminde Günlük Görev Kısıtlamasının İncelenmesi

Yıl 2021, Sayı: 28, 207 - 212, 30.11.2021

Engin Pekel

https://doi.org/10.31590/ejosat.995415

Öz

Bu makale, farklı bir konsepte sahip çok dönemli bir teknisyen rotalama ve programlama problemini ele almaktadır. Sorun, çeşitli becerilere sahip teknisyenlerin ekipler oluşturması ve bu ekiplerin farklı konumlarda yapılan görevleri yerine getirmesidir. Teknisyenlerin görevleri yerine getirirken günlük görev kapasiteleri vardır. Farklı teknisyen numaralarının birleştirilmesiyle fazla mesai maliyetlerine izin verilen durumlar analiz edilmiştir. Çalışma, problemi modellemek için tek amaçlı bir karma tamsayı programlama yöntemi sağlar, çünkü uygulanan model ulaşım maliyetini optimize ederken aynı zamanda fazla çalışma miktarını da en aza indirmeyi amaçlar. Ana konu ayrıca farklı becerilere sahip teknisyenlerin ekiplere bölünmesini, farklı beceri gereksinimlerine sahip görevlerin ekiplere atanmasını ve her ekip için aynı anda rotaları belirtir. Günlük uğranan müşteri sayısı belirlenen limit dahilinde gerçekleşir. Ayrıca model, günlük müşteri limitinin aşılmasını da modele dahil etmiş ve bir kısıtlamaya bağlamıştır. Müşterilerin günlük normal ve fazla çalışma sayılarının çeşitli kombinasyonları değerlendirilmiş ve amaç fonksiyonu üzerindeki etkileri incelenmiştir. Son olarak, makale, önerilen matematiksel formülasyon ve çözüm yaklaşımının etkinliğini değerlendirmek için hesaplamalı deneyler ve analizler sunar. Sonuçlar, günlük görev kısıtlamalarının çalışan seçiminde ve kullanım miktarında etkili olduğunu göstermektedir.

Anahtar Kelimeler

Dal ve sınır, Çok periyotlu, Minimizasyon, Teknisyen çizelgeleme, Teknisyen rotalama

Examination of Daily Task Constraint in Technician Routing and Scheduling Problem

Öz

This paper deals with a multi-term technician routing and programming problem with a different concept. The problem is that technicians with various skills form teams, and these teams perform the tasks that take in distinct locations. Technicians have daily duty capacities while performing tasks. The cases where overtime costs are allowed by combining different technician numbers are analyzed. Paper provides a single-purpose mixed integer programming method for modeling the problem because the model implemented aims to optimize the travel cost while simultaneously minimizing the amount of overwork. The main issue also specifies the division of technicians with different skills into teams, assignment of tasks with different skill requirements to teams, and routes for each team at the same time. The number of customers visited on a route within the daily customer limit. In addition, the model included exceeding the daily customer limit in the model and bound it to a constraint. The various combinations of the daily normal and over-work number of customers were evaluated and examined their effects on the objective function. Finally, the paper presents computational experiments and analyses to evaluate the efficiency of the proposed mathematical formulation and solution approach. The results show that daily task constraints are effective in employee selection and amount of use.

Anahtar Kelimeler

Branch and bound, Minimization, Multi period, Technician routing, Technician scheduling

Kaynakça

• B. Moradi, The new optimization algorithm for the vehicle routing problem with time windows using multi-objective discrete learnable evolution model. Soft Computing, 2019. p.1-29.
• A.A. Kovacs, S.N Parragh, K.F. Doerner, and R.F. Hartl, Adaptive large neighborhood search for service technician routing and scheduling problems, J Scheduling, 2012. 15, p.579-600.
• V. Pillac, C. Gueret, and A.L. Medaglia, A parallel matheuristic for the technician routing and scheduling problem, Optimization Letters, 2013. 7, p.1525-1535.
• A. Dohn, E. Kolind, and J. Clausen, The manpower allocation problem with time windows and job-teaming constraints: A branch-and-price approach, Computers and Operations Research, 2009. 36, p.1145-1157.
• J.F. Cordeau, G. Laporte, F. Pasin, and S. Ropke, Scheduling technicians and tasks in a telecommunications company, Journal of Scheduling, 2010. 13, p.393-409.
• S. Bertels, and T. Fahle, A hybrid setup for a hybrid scenario: combining heuristics for the home health care problem, Computers and Operations Research, 2006. 33, p.2866-2890.
• J.Y. Xu, and S.Y Chiu, Effective heuristic procedures for a field technician scheduling problem, Journal of Heuristics, 2001. 7, p.495-509.
• H. Tang, E. Miller-Hooks, and R. Tomastik, Scheduling technicians for planned maintenance of geographically distributed equipment, Transportation Research Part E: Logistics and Transportation Review, 2007. 43, p.591-609.
• X. Chen, M. Hewitt, and B.W Thomas, An approximate dynamic programming method for the multi-period technician scheduling problem with experience-based service times and stochastic customers, Internation Journal of Production Economics, 2018. 196, p.122-134.
• I. Lazakis, and S. Khan, An optimization framework for daily route planning and scheduling of maintenance vessel activities in offshore wind farms. Ocean Engineering, 2021. 225, 108752.
• S. Çakırgil, E. Yücel, and G. Kuyzu, An integrated solution approach for multi-objective, multi-skill workforce scheduling and routing problems. Computers & Operations Research, 2020. 118, 104908.
• I. Mathlouthi, M. Gendreau, and J.Y. Potvin, A metaheuristic based on Tabu search for solving a technician routing and scheduling problem. Computers & Operations Research, 2021. 125, 105079.
• C.A. Irawan, M. Eskandarpour, D. Ouelhadj, and D. Jones, Simulation-based optimisation for stochastic maintenance routing in an offshore wind farm. European Journal of Operational Research, 2021. 289(3), p.912-926.
• B. Graf, Adaptive large variable neighborhood search for a multiperiod vehicle and technician routing problem. Networks, 2020. 76(2), p.256-272.
• S. Frifita, I. Mathlouthi, and A. Dammak, An Efficient VNS Algorithm to Solve the Multi-Attribute Technician Routing and Scheduling Problem. International Journal of Applied Metaheuristic Computing (IJAMC), 2020. 11(1), p.23-35.
• A. Khalfay, A. Crispin, and K. Crockett, (2019, September). Solving the service technician routing and scheduling problem with time windows. In Proceedings of SAI Intelligent Systems Conference (p. 1168-1177). Springer, Cham.
• E. Pekel, Solving technician routing and scheduling problem using improved particle swarm optimization. Soft Computing, 2020. 24(24), 19007-19015.
• E. Pekel. and S.S. Kara, Solving fuzzy capacitated location routing problem using hybrid variable neighborhood search and evolutionary local search. Applied Soft Computing, 2019. 83, 105665.
• E. Zamorano, and R. Stolletz, Branch-and-price approaches for the multiperiod technician routing and scheduling problem. European Journal of Operational Research, 2017. 257(1), 55-68.
• K. Kianfar, Branch‐and‐Bound Algorithms. Wiley Encyclopedia of Operations Research and Management Science. 2010.