ارائه مدل حمل و نقل هزینه ثابت پله‌ای، چند محصولی، دوسطحی و حل آن با الگوریتم شبیه‌سازی تبرید

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانش آموخته کارشناسی ارشد، دانشکده مهندسی صنایع، پردیس دانشکده‌های فنی، دانشگاه تهران، ایران

2 استاد، دانشکده مهندسی صنایع، پردیس دانشکده‌های فنی، دانشگاه تهران، ایران

3 دانشجوی دکتری، دانشکده مهندسی صنایع، دانشگاه علم و صنعت ایران، تهران، ایران

4 استادیار، گروه مهندسی صنایع، دانشگاه علم و فناوری مازندران، بهشهر، ایران

چکیده

در دنیای واقعی معمولا علاوه بر هزینه متغیر حمل و نقل که وابسته به مقدار حمل‌شده است، هزینه ثابت دیگری برای استفاده از هر مسیر وجود دارد. این مسأله به عنوان حمل و نقل هزینه ثابت(FCTP)، یک مسأله برنامه‌ریزی است که در صنعت و تجارت به صورت عملی مورد توجه شایانی قرار گرفته است. در سال‌های اخیر نوع خاصی از هزینه ثابت، به صورت پله‌ای معرفی شده است که در این زمینه مطالعات محدودی صورت گرفته است که صرفا شامل مسائل تک سطحی، با یک محصول و یک نوع وسیله نقلیه است.در این مقالهحمل و نقل هزینه ثابت به صورت پله­ای دوسطحی، برای چند محصول، چند نوع وسیله نقلیه (مسأله solid) و با در نظرگیری محدودیت ظرفیت روی مسیر و وسایل نقلیه مدل­سازی و حل شده است. با توجه به NP-hardبودن مسأله، برای حل مدل، الگوریتم فراابتکاری شبیه­سازی تبرید (SA) استفاده شده است. جهت ارزیابی کارایی این الگوریتم، نتایج حل آن با نتایج حل دقیق به دست آمده از حل نرم افزار GAMS مقایسه گردیده و نتایج نشان می‌دهد الگوریتم SA جواب‌های نسبتا خوبی در مدت زمان مناسب ارائه می‌دهد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

A Two-Stage, Multi-Commodity, Step Fixed-Charge Transportation Model Solving by a Simulated Annealing Algorithm

نویسندگان [English]

  • Hosna Molanoori 1
  • Reza Tavakkoli-Moghaddam 2
  • Fatemeh Sabouhi 3
  • Mostafa Hajiaghaiee Keshteli 4
1 MSc., Grad., Department of Industrial Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran
2 Professor, Department of Industrial Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran
3 Ph.D. Student, Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
4 Assistant Professor, Department of Industrial Engineering, Mazandaran University of Science and Technology, Behshahr, Iran
چکیده [English]

In real life situations, in addition to the variable cost, there is another cost incurred for opening each route, which is known as fixed cost. This problem as the fixed-charge transportation has attracted considerable attention in an industry and business. In recent years, a certain type of a fixed charge is presented as step fixed-charge. Few studies have been done concerning a step fixed-charge transportation problem (SFCTP) that only include single level distribution of a single commodity, in which there is only one kind of a vehicle. In this paper, the capacitated, solid, two-stage SFCTP is modeled. Because this problem is considered to be an NP-hard one, a simulated annealing algorithm (SA) is proposed to solve the new presented model. To evaluate the performance of the SA algorithm, the results are compared to an exact solution obtained by using GAMS. The results show that the SA algorithm provides relatively good solutions in a reasonable time.

کلیدواژه‌ها [English]

  • Step fixed-charge transportation
  • solid
  • two-stage supply chain
  • simulated annealing
-  Altassan, K. M., El-Sherbiny, M. M. and Sasidhar, B. (2013) “Near optimal solution for the step fixed charge transportation problem”, Applied Mathematics and Information Sciences, Vol. 7, No. 2, January, pp. 661-669.
-  Balaji, A. N. and Jawahar, N. (2010) “A simulated annealing algorithm for a two-stage fixed charge distribution problem of a supply chain”, International Journal of Operational Research, Vol. 7, No. 2, January, pp. 192-215.
-  Balinski, M. L. (1961) “Fixed‐cost transportation problems”, Naval Research Logistics Quarterly, Vol. 8, No. 1, March, pp. 41-54.
-  Barzinpour, F., Saffarian, M., Makoui, A. and Teimoury, E. (2014). “Metaheuristic algorithm for solving bi-objective possibility planning model of location-allocation in disaster relief logistics”, Journal of Applied Mathematics, Vol. 2014, Article ID 239868, April, pp. 1-17.
-  Busetti, F. (2003) “Simulated annealing overview”, JP Morgan, Italy.
-  Ekşioğlu, S. D., Ekşioğlu, B. and Romeijn, H. E. (2007). “A Lagrangean heuristic for integrated production and transportation planning problems in a dynamic, multi-item, two-layer supply chain”, IIE Transactions, Vol. 39, No. 2, February, pp. 191-201.
-  El-Sherbiny, M. M. (2012) “Alternate mutation based artificial immune algorithm for step fixed charge transportation problem”, Egyptian Informatics Journal, Vol. 13, No. 2, July, pp. 123-134.
-  El-Sherbiny, M. M. and Alhamali, R. M. (2013) “A hybrid particle swarm algorithm with artificial immune learning for solving the fixed charge transportation problem”, Computers and Industrial Engineering, Vol. 64, No. 2, February, pp. 610-620.
-  Giri, P. K., Maiti, M. K.and Maiti, M. (2015). “Fully fuzzy fixed charge multi-item solid transportation problem”, Applied Soft Computing,‏Vol. 2015, No. 27, February,  pp. 77-91
-  Hajiaghaei-Keshteli, M., Molla-Alizadeh-Zavardehi, S. and Tavakkoli-Moghaddam, R. (2010) “Addressing a nonlinear fixed-charge transportation problem using a spanning tree-based genetic algorithm”, Computers and Industrial Engineering, Vol. 59, No. 2, September, pp. 259-271.
-  Jo, J. B., Li, Y. and Gen, M. (2007) “Nonlinear fixed charge transportation problem by spanning tree-based genetic algorithm”, Computers and Industrial Engineering, Vol. 53, No. 2, September, pp. 290-298.
-  Kannan, D., Govindan, K. and Soleimani, H. (2014) “Artificial immune system and sheep flock algorithms for two-stage fixed-charge transportation problem”, Optimization, Vol. 63, No. 10, October, PP. 1465-1479.
-  Kowalski, K. and Lev, B. (2008) “On step fixed-charge transportation problem”, Omega, Vol. 36, No. 5, October, pp. 913-917.
-  Kumar, P. R. (2014) “On modeling the step fixed charge transportation problem”, International Conference on Technology and Business Management, March, pp. 1-26.
-  Manimaran, P. and Selladurai, V. (2014) “Cat swarm optimization for single stage supply chain distribution system with fixed charges”, ICTACT Journal on Soft Computing, Vol. 4, No. 2, January, pp. 687-691.
-  Molla-Alizadeh-Zavardehi, S., Mahmoodirad, A. and Rahimian, M. (2014) “Step fixed charge transportation problems via genetic algorithm”, Indian Journal of Science and Technology, Vol. 7, No. 7, July, pp. 949-954.
-  Pintea, C. M. and Pop, P. C. (2015) “An improved hybrid algorithm for capacitated fixed-charge transportation problem”, Logic Journal of IGPL. Vol. 23, No. 3, pp. 369-378.
-  Pramanik, S., Jana, D. K., Mondal, S. K. and Maiti, M. (2015)  “A fixed-charge transportation problem in two-stage supply chain network in Gaussian type-2 fuzzy environments”,  Information Sciences, No. 325, December, pp. 190-214.
-  Ruiz, R. and Stützle, T. (2007) “A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem”, European Journal of Operational Research, Vol. 177, No. 3, March, pp. 2033-2049.
-  Sandrock, K. (1988) “A simple algorithm for solving small, fixed-charge transportation problems”, Journal of the Operational Research Society, No. 39, May, pp. 467-475.
-  Thiongane, B., Cordeau, J. F. and Gendron, B. (2015) “Formulations for the non-bifurcated hop-constrained multi-commodity capacitated fixed-charge network design‌ problem”, Computers and Operations Research, Vol. 2015, No. 53, January, pp. 1-8.
Torabi, S. A. and Hassini, E. (2008) “An interactive possibilistic programming approach for multiple objective supply chain master planning”. Fuzzy Sets and Systems, Vol. 159, No. 2, January, pp. 193-214.