# American Institute of Mathematical Sciences

January  2008, 4(1): 53-66. doi: 10.3934/jimo.2008.4.53

## A mixed simulated annealing-genetic algorithm approach to the multi-buyer multi-item joint replenishment problem: advantages of meta-heuristics

 1 Diocesan Girls' School, Kowloon, Hong Kong, China 2 Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China 3 Graduate School of Management, Kent State University, Kent, OH 44244, United States

Received  August 2006 Revised  December 2006 Published  January 2008

The Joint Replenishment Problem (JRP) is a multi-item inventory problem. The objective is to develop inventory policies that minimize total cost (comprised of holding and setup costs) over the planning horizon. In this paper we consider the extension of this problem to the multi-buyer, multi-item version of the JRP. We propose and test a mixed simulated annealing-genetic algorithm (SAGA) for the extended problem. Tests are conducted on problems from a leading bank in Hong Kong. Results are also compared to a pure GA approach and several interesting observations are made on the value of such meta-heuristics.
Citation: T. W. Leung, Chi Kin Chan, Marvin D. Troutt. A mixed simulated annealing-genetic algorithm approach to the multi-buyer multi-item joint replenishment problem: advantages of meta-heuristics. Journal of Industrial and Management Optimization, 2008, 4 (1) : 53-66. doi: 10.3934/jimo.2008.4.53
 [1] Lan Luo, Zhe Zhang, Yong Yin. Simulated annealing and genetic algorithm based method for a bi-level seru loading problem with worker assignment in seru production systems. Journal of Industrial and Management Optimization, 2021, 17 (2) : 779-803. doi: 10.3934/jimo.2019134 [2] Yukang He, Zhengwen He, Nengmin Wang. Tabu search and simulated annealing for resource-constrained multi-project scheduling to minimize maximal cash flow gap. Journal of Industrial and Management Optimization, 2021, 17 (5) : 2451-2474. doi: 10.3934/jimo.2020077 [3] Li Deng, Wenjie Bi, Haiying Liu, Kok Lay Teo. A multi-stage method for joint pricing and inventory model with promotion constrains. Discrete and Continuous Dynamical Systems - S, 2020, 13 (6) : 1653-1682. doi: 10.3934/dcdss.2020097 [4] Jingwen Zhang, Wanjun Liu, Wanlin Liu. An efficient genetic algorithm for decentralized multi-project scheduling with resource transfers. Journal of Industrial and Management Optimization, 2022, 18 (1) : 1-24. doi: 10.3934/jimo.2020140 [5] Wenpin Tang, Xun Yu Zhou. Tail probability estimates of continuous-time simulated annealing processes. Numerical Algebra, Control and Optimization, 2022  doi: 10.3934/naco.2022015 [6] Ashkan Ayough, Farbod Farhadi, Mostafa Zandieh, Parisa Rastkhadiv. Genetic algorithm for obstacle location-allocation problems with customer priorities. Journal of Industrial and Management Optimization, 2021, 17 (4) : 1753-1769. doi: 10.3934/jimo.2020044 [7] Ming-Jong Yao, Tien-Cheng Hsu. An efficient search algorithm for obtaining the optimal replenishment strategies in multi-stage just-in-time supply chain systems. Journal of Industrial and Management Optimization, 2009, 5 (1) : 11-32. doi: 10.3934/jimo.2009.5.11 [8] Chenyin Wang, Yaodong Ni, Xiangfeng Yang. The inventory replenishment policy in an uncertain production-inventory-routing system. Journal of Industrial and Management Optimization, 2021  doi: 10.3934/jimo.2021196 [9] Jiao-Yan Li, Xiao Hu, Zhong Wan. An integrated bi-objective optimization model and improved genetic algorithm for vehicle routing problems with temporal and spatial constraints. Journal of Industrial and Management Optimization, 2020, 16 (3) : 1203-1220. doi: 10.3934/jimo.2018200 [10] Ming-Jong Yao, Yu-Chun Wang. Theoretical analysis and a search procedure for the joint replenishment problem with deteriorating products. Journal of Industrial and Management Optimization, 2005, 1 (3) : 359-375. doi: 10.3934/jimo.2005.1.359 [11] Gaurav Nagpal, Udayan Chanda, Nitant Upasani. Inventory replenishment policies for two successive generations price-sensitive technology products. Journal of Industrial and Management Optimization, 2022, 18 (3) : 1629-1650. doi: 10.3934/jimo.2021036 [12] Mostafa Abouei Ardakan, A. Kourank Beheshti, S. Hamid Mirmohammadi, Hamed Davari Ardakani. A hybrid meta-heuristic algorithm to minimize the number of tardy jobs in a dynamic two-machine flow shop problem. Numerical Algebra, Control and Optimization, 2017, 7 (4) : 465-480. doi: 10.3934/naco.2017029 [13] Yaw Chang, Lin Chen. Solve the vehicle routing problem with time windows via a genetic algorithm. Conference Publications, 2007, 2007 (Special) : 240-249. doi: 10.3934/proc.2007.2007.240 [14] Didem Cinar, José António Oliveira, Y. Ilker Topcu, Panos M. Pardalos. A priority-based genetic algorithm for a flexible job shop scheduling problem. Journal of Industrial and Management Optimization, 2016, 12 (4) : 1391-1415. doi: 10.3934/jimo.2016.12.1391 [15] Abdel-Rahman Hedar, Alaa Fahim. Filter-based genetic algorithm for mixed variable programming. Numerical Algebra, Control and Optimization, 2011, 1 (1) : 99-116. doi: 10.3934/naco.2011.1.99 [16] Bin Zhou, Xinghao Chen. A directional heuristics pulse algorithm for a two resources constrained shortest path problem with reinitialization. Journal of Industrial and Management Optimization, 2022  doi: 10.3934/jimo.2022097 [17] Maryam Ghoreishi, Abolfazl Mirzazadeh, Gerhard-Wilhelm Weber, Isa Nakhai-Kamalabadi. Joint pricing and replenishment decisions for non-instantaneous deteriorating items with partial backlogging, inflation- and selling price-dependent demand and customer returns. Journal of Industrial and Management Optimization, 2015, 11 (3) : 933-949. doi: 10.3934/jimo.2015.11.933 [18] Kazeem Olalekan Aremu, Chinedu Izuchukwu, Grace Nnenanya Ogwo, Oluwatosin Temitope Mewomo. Multi-step iterative algorithm for minimization and fixed point problems in p-uniformly convex metric spaces. Journal of Industrial and Management Optimization, 2021, 17 (4) : 2161-2180. doi: 10.3934/jimo.2020063 [19] Behrouz Kheirfam, Morteza Moslemi. On the extension of an arc-search interior-point algorithm for semidefinite optimization. Numerical Algebra, Control and Optimization, 2018, 8 (2) : 261-275. doi: 10.3934/naco.2018015 [20] Jussi Toivanen, Alexander Meaney, Samuli Siltanen, Ville Kolehmainen. Joint reconstruction in low dose multi-energy CT. Inverse Problems and Imaging, 2020, 14 (4) : 607-629. doi: 10.3934/ipi.2020028

2021 Impact Factor: 1.411

## Metrics

• PDF downloads (71)
• HTML views (0)
• Cited by (1)

## Other articlesby authors

• on AIMS
• on Google Scholar

[Back to Top]