طراحی مدل زمان‌بندی کامیون‌ها در سیستم انبار عبوری موقت چند دربه با رویکرد توقف عملیات

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، دانشکده مدیریت و حسابداری، دانشگاه شهید بهشتی، تهران، ایران

2 استادیار، دانشکده مدیریت و حسابداری، دانشگاه شهید بهشتی، تهران، ایران

3 استاد، دانشکده مدیریت و حسابداری، دانشگاه شهید بهشتی، تهران، ایران

4 دانشیار، دانشکده مدیریت و حسابداری، دانشگاه شهید بهشتی، تهران، ایران

چکیده

انبار عبوری موقت  یک استراتژی توزیع در زنجیره تأمین است که در آن، کالاها و محصولات به‌طور مستقیم از قسمت دریافت به قسمت ارسال منتقل می‌شوند؛ بدون اینکه در مرکز توزیع یا انبار نگه‌داری شوند. هدف این تحقیق، طراحی مدل زمان‌بندی کامیون‌ها در سیستم انبار عبوری موقت چند دربه با رویکرد توقف عملیات است. در این سناریو از زمان‌بندی انبار عبوری موقت، کامیون‌ها مجاز هستند که در حین فعالیت تخلیه و بارگیری متوقف شوند و درزمانی دیگر، فعالیت را از سر بگیرند (رویکرد توقف عملیات ). بنابراین، هم کامیون‌های ورودی و هم کامیون‌های خروجی می‌توانند به‌صورت متناوب داخل و خارج انبار شوند. برای این سناریو، یک مدل برنامه‌ریزی عدد صحیح مختلط خطی توسعه داده شده است. علاوه بر مدل ریاضی، با توجه به ماهیت پیچیده این مسائل، سه الگوریتم فرا‌ابتکاری  برای حل آن و ساختار جدیدی برای نمایش جواب مسئله پیشنهاد شده است. همچنین به‌منظور افزایش کارایی الگوریتم‌ها، از روش تنظیم پارامتر تاگوچی  استفاده شده است. نتایج تجربی نشان می‌دهند که الگوریتم ژنتیک  از دو الگوریتم دیگر (شبیه‌سازی تبرید  و جستجوی ممنوعه ) عملکرد بهتری داشته است.

کلیدواژه‌ها


عنوان مقاله [English]

Truck Scheduling in Distribution Systems with Multiple Cross Docks and No Intermediate Storage

نویسندگان [English]

  • mahdieh bagher 1
  • masoud kassaee 2
  • Akbar Alem Tabriz 3
  • mostafa zandieh 4
1 PhD. student, faculty of Management and Accounting, Shahid Beheshti University, Tehran, Iran.
2 Associate Professor, faculty of Management and Accounting, Shahid Beheshti University, Tehran, Iran.
3 Professor, faculty of Management and Accounting, Shahid Beheshti University, Tehran, Iran.
4 Associate Professor, faculty of Management and Accounting, Shahid Beheshti University, Tehran, Iran.
چکیده [English]

Cross docking is a new strategy in supply chain management. In a cross docking system, items move directly from receiving dock to shipping dock, without being stored in the warehouse or distribution center. This paper studies the problem of truck scheduling in a distribution system including multiple cross docks with no intermediate storage. In this model of cross docking scenario preemption of trucks is allowed. Therefore, both inbound and outbound trucks can arrive and move out the distribution center intermittently. In this paper a mixed integer linear programming model has been developed. Moreover, to solve the problem we proposed three metaheuristics algorithm based on tabu search, simulated annealing and genetic algorithm. In this regard, we propose a novel solution encoding scheme for the problem. And the algorithms are tuned by Taguchi method. Using numerical experiments, the genetic algorithm outperforms the other two algorithms Besides.

کلیدواژه‌ها [English]

  • multi docks cross
  • truck scheduling
  • metaheuristics
[1]     Apte UM, Viswanathan S. (2000). Effective cross docking for improving distribution efficiencies. International Journal of Logistics: Research and Applications, 3(3), 291–302.
[2]     Yu W, (2002), Operational strategies for cross docking systems, Dissertation, Iowa state University, Ames, IA, USA.
[3]     Boysen N, and Fliedner M, (2010), Cross dock scheduling: Classification, literature review and research agenda, Omega, 38, 413–422.
[4]     Boysen N, (2010), Truck scheduling at zero-inventory cross docking terminals, Computers and Operations Research, 37, 32–41.
[5]     Vahdani B, Zandieh M, (2010), Scheduling trucks in cross-docking systems: robust meta-heuristics, Computers and Industrial Engineering, 58(1), 12–24.
[6]     Yu W, and Pius J. E, (2008), Scheduling of inbound trucks in cross docking systems with temporary storage, European Journal of Operational Research, 184(1), 377–396.
[7]     Arabani ARB, Ghomi SMTF, Zandieh M, (2011), Meta-heuristics implementation for scheduling of trucks in a cross-docking system with temporary storage, Expert Systems with Applications, 38(3), 1964–79.
[8]     Forouharfard S, Zandieh M, (2010), An imperialist competitive algorithm to schedule of receiving and shipping trucks in cross-docking systems, The International Journal of Advanced Manufacturing Technology, 51(9), 1179–93.
[9]     Arabani ARB, Ghomi SMTF, Zandieh M, (2010), A multi-criteria cross-docking scheduling with just-in-time approach, The International Journal of Advanced Manufacturing Technology, 49(5), 741–56.
[10] Boloori Arabani A, Zandieh M, and Fatemi Ghomi S.M.T, (2012), A cross-docking scheduling problem with sub-population multi-objective algorithms, The International Journal of Advanced Manufacturing Technology, 58, 741–761.
[11] Boloori Arabani, A. R., Zandieh, M., & Fatemi Ghomi, S. M. T, (2011), Mulit-objective genetic-based algorithms for a cross-docking scheduling problem, Applied Soft Computing, 11, 1954–4970.
[12] Boysen N, Fliedner M, and Scholl A, (2010), Scheduling inbound and outbound trucks at cross docking terminals. OR Spectrum, 32, 135–161.
[13] Vahdani B, Soltani R, and Zandieh M, (2009), Scheduling the truck holdover recurrent dock cross-dock problem using robust meta-heuristics, International Journal of Advanced Manufacturing Technology, 46, 769-783.
[14] Soltani R, Sadjadi SJ, (2010), Scheduling trucks in cross-docking systems: a robust meta-heuristics approach, Transportation Research Part E: Logistics and Transportation Review, 46(5), 650–66.
[15] Van Belle J, Valckenaers P, and Cattrysse D, (2012), Cross-docking: State of the art, Omega, 40, 827–846.
[16] Belle J V, Valckenaers P, Berghe G V, and Cattrysse D, (2013), A tabu search approach to the truck scheduling problem with multiple docks and time windows, Computers and Industrial Engineering, 66(4), 818–826.
[17] Joo C M, and Kim B S, (2013), Scheduling compound trucks in multi-door cross-docking terminals, International Journal of Advanced Manufacturing Technology, 64, 977–988.
[18] Madani-Isfahani M, Tavakoli-Moghaddam R, Naderi B, (2010), Multiple cross-docks scheduling using two meta-heuristic algorithms, Computers and Industrial Engineering, S0360-8352(14)00154-5.
[19] Miao Z, Lim A, and Ma H, (2009), Truck dock assignment problem with operational time constraint within cross docks, European Journal of Operational Research, 192, 105–115.
[20] Liao T, Egbelu P J, and Chang P C, (2013), Simultaneous dock assignment and sequencing of inbound trucks under a fixed outbound truck schedule in multi door cross docking operations, International Journal of Production Economics,141, 212–229.
[21] Lee  K, Kim B S, and Joo C M, (2012), Genetic algorithms for door-assigning and sequencing of trucks at distribution centers for the improvement of operational performance, Expert Systems with Applications, 39, 12975–12983.
[22] Konur D, and Golias M M, (2013), Analysis of different approaches to cross-dock truck scheduling with truck arrival time uncertainty, Computers and Industrial Engineering, 65(4), 663–672.
[23] Kuo Y, (2013), Optimizing truck sequencing and truck dock assignment in a cross docking system, Expert Systems with Applications, 40(14), 5532-5541.
[24] Chen F, Lee CY, (2009), Minimizing the makespan in a two-machine cross-docking flow shop problem, European Journal of Operational Research, 193(1), 59–72.
[25] Amiri M,Taghavi fard M, and Aghaei M, (2016), Development of three-objective model for the location – allocation of assistance centers in a probabilistic condition of availability to emergency vehicles, Modern Researches in Decision making, 1(2), 1-27.
[26] Notash M, Zandieh M, and Dorri Nokarani B, (2015), Using a Genetic algorithm approach for designing multi-objective supply chain network, Management Researches in Iran, 4(18), 183-203.
[27] Glover F, (1989), Tabu search. Part I ORSA Journal on Computing, 1, 190–206.
[28] Kirkpatrick S, Gelatt C D, Vecchi M P, (1983), Optimization by simulated annealing, Science 220 (4598), 671–680.
[29] Holland JH, (1975), Adaptation in natural and artificial systems, University of Michigan Press, Ann Arbor, IL.
[30] Taguchi G, (1986), Introduction to quality engineering, White Plains: Asian Productivity Organization.