Synchronized scheduling of production and outbound shipping using bilevel-based simulated annealing algorithm

Abstract In general, different divisions even in a same company may make scheduling decisions irrespective of the overall benefit of the company. It is practically impossible to carry out the integrated optimization, and the sequential optimization results in isolated solutions within the divisions often leads to inferior overall solutions. In this study, a novel bilevel approach is proposed for joint synchronized production and shipping scheduling, considering production division as the leader and shipping division as the follower. A bilevel-based simulating annealing (SA) algorithm is proposed as the solution algorithm. Specifically, first, the production division prepares a tentative production schedule obtained by the SA. Based on the tentative schedule, shipping scheduling is addressed by an effective heuristic named Earliest Completion Machine. An inner SA is also presented for shipping scheduling to generate good quality shipping schedules. The tentative schedule is iteratively updated until the stopping criterion is satisfied. The effectiveness and efficiency of the proposed approach were verified via comparison with the traditional sequential and integrated approaches. Furthermore, the sensitivity analysis results indicate that shipping capacity has a considerable effect on the overall makespan. The allocation of the fixed shipping capacity onto blocks was also investigated, indicating that the large more strategy outperforms the average allocation and the large less strategies.

[1]  H. Cohn,et al.  Simulated Annealing: Searching for an Optimal Temperature Schedule , 1999, SIAM J. Optim..

[2]  Patrice Marcotte,et al.  An overview of bilevel optimization , 2007, Ann. Oper. Res..

[3]  Hecheng Li,et al.  An Evolutionary Algorithm for Solving Bilevel Programming Problems Using Duality Conditions , 2012 .

[4]  Bothina El-Sobky,et al.  A penalty method with trust-region mechanism for nonlinear bilevel optimization problem , 2018, J. Comput. Appl. Math..

[5]  Zhi-Long Chen,et al.  Integrated Production and Outbound Distribution Scheduling: Review and Extensions , 2010, Oper. Res..

[6]  Mostafa Hajiaghaei-Keshteli,et al.  Genetic algorithms for coordinated scheduling of production and air transportation , 2010, Expert Syst. Appl..

[7]  Hideo Tanaka,et al.  Modified simulated annealing algorithms for the flow shop sequencing problem , 1995 .

[8]  Chien-Hung Lin,et al.  Makespan minimization for two uniform parallel machines , 2003 .

[9]  Kathryn E. Stecke,et al.  Production and Transportation Integration for a Make-to-Order Manufacturing Company with a Commit-to-Delivery Business Mode , 2007, Manuf. Serv. Oper. Manag..

[10]  Amir Hossein Alavi,et al.  Behavior of crossover operators in NSGA-III for large-scale optimization problems , 2020, Inf. Sci..

[11]  Ariel Rubinstein,et al.  A Course in Game Theory , 1995 .

[12]  Hisao Ishibuchi,et al.  Multi-clustering via evolutionary multi-objective optimization , 2018, Inf. Sci..

[13]  Herminia I. Calvete,et al.  Bilevel model for production-distribution planning solved by using ant colony optimization , 2011, Comput. Oper. Res..

[14]  Feng Chu,et al.  A Stackelberg game and its improvement in a VMI system with a manufacturing vendor , 2009, Eur. J. Oper. Res..

[15]  Guoqing Wang,et al.  Parallel machine scheduling with batch delivery costs , 2000 .

[16]  Bruce E. Hajek,et al.  Cooling Schedules for Optimal Annealing , 1988, Math. Oper. Res..

[17]  Sigrid Knust,et al.  Tabu search and lower bounds for a combined production-transportation problem , 2013, Comput. Oper. Res..

[18]  Chris N. Potts,et al.  The Coordination of Scheduling and Batch Deliveries , 2005, Ann. Oper. Res..

[19]  Hong Zhou,et al.  An extended branch and bound algorithm for linear bilevel programming , 2006, Appl. Math. Comput..

[20]  R. Yang,et al.  Convergence of the Simulated Annealing Algorithm for Continuous Global Optimization , 2000 .

[21]  Shih-Wei Lin,et al.  A multi-point simulated annealing heuristic for solving multiple objective unrelated parallel machine scheduling problems , 2015 .

[22]  Panos M. Pardalos,et al.  A new bilevel formulation for the vehicle routing problem and a solution method using a genetic algorithm , 2007, J. Glob. Optim..

[23]  Hao Luo,et al.  Synchronisation of production scheduling and shipment in an assembly flowshop , 2015 .

[24]  Ceyda Oguz,et al.  Parallel machine scheduling with additional resources: Notation, classification, models and solution methods , 2013, Eur. J. Oper. Res..

[25]  Michael Pinedo,et al.  Scheduling: Theory, Algorithms, and Systems , 1994 .

[26]  Christos Koulamas,et al.  Makespan minimization on uniform parallel machines with release times , 2004, Eur. J. Oper. Res..

[27]  Rudolf Müller,et al.  Games and Mechanism Design in Machine Scheduling—An Introduction , 2007 .

[28]  Helio J. C. Barbosa,et al.  A study on the use of heuristics to solve a bilevel programming problem , 2015, Int. Trans. Oper. Res..

[29]  Ling Wang,et al.  Comprehensive learning pigeon-inspired optimization with tabu list , 2019, Science China Information Sciences.

[30]  Zrinka Lukac,et al.  Production planning problem with sequence dependent setups as a bilevel programming problem , 2004, Eur. J. Oper. Res..

[31]  George L. Vairaktarakis,et al.  Integrated Scheduling of Production and Distribution Operations , 2005, Manag. Sci..