Models and algorithms for production planning, scheduling and sequencing problems: A holistic framework and a systematic review

Makui, 2016, Accelerating Benders decomposition approach for robust aggregate production planning of products with a very limited expiration date, Comput. Ind. Eng., 100, 34, 10.1016/j.cie.2016.08.005 Nam, 1992, Aggregate production planning - A survey of models and methodologies, Eur. J. Oper. Res., 61, 255, 10.1016/0377-2217(92)90356-E Cheraghalikhani, 2019, Aggregate production planning: a literature review and future research directions, Int. J. Ind. Eng. Comput., 10, 309 Jamalnia, 2019, Aggregate production planning under uncertainty: a comprehensive literature survey and future research directions, Int. J. Adv. Manuf. Technol., 102, 159, 10.1007/s00170-018-3151-y Mula, 2006, Models for production planning under uncertainty: a review, Int. J. Prod. Econ., 103, 271, 10.1016/j.ijpe.2005.09.001 Díaz-Madroñero, 2014, A review of discrete-time optimization models for tactical production planning, Int. J. Prod. Res., 52, 5171, 10.1080/00207543.2014.899721 Mundi, 2019, Review of mathematical models for production planning under uncertainty due to lack of homogeneity: proposal of a conceptual model, Int. J. Prod. Res., 7543, 1 Lage, 2012, Production planning and control for remanufacturing: literature review and analysis, Prod. Plan. Control, 23, 419, 10.1080/09537287.2011.561815 Mula, 2010, Mathematical programming models for supply chain production and transport planning, Eur. J. Oper. Res., 204, 377, 10.1016/j.ejor.2009.09.008 Akçcal, 2011, Quantitative models for inventory and production planning in closed-loop supply chains, Int. J. Prod. Res., 49, 2373, 10.1080/00207541003692021 Peidro, 2009, Quantitative models for supply chain planning under uncertainty, Int. J. Adv. Manuf. Technol., 43, 400, 10.1007/s00170-008-1715-y Stindt, 2014, Review of research on closed loop supply chain management in the process industry, Flex. Serv. Manuf. J., 26, 268, 10.1007/s10696-012-9137-4 Govindan, 2015, Reverse logistics and closed-loop supply chain: a comprehensive review to explore the future, Eur. J. Oper. Res., 240, 603, 10.1016/j.ejor.2014.07.012 Fahimnia, 2015, Quantitative models for managing supply chain risks: a review, Eur. J. Oper. Res., 247, 1, 10.1016/j.ejor.2015.04.034 Seuring, 2008, From a literature review to a conceptual framework for sustainable supply chain management, J. Clean. Prod., 16, 1699, 10.1016/j.jclepro.2008.04.020 Seuring, 2012, Conducting content-analysis based literature reviews in supply chain management, Supply Chain Manag, 17, 544, 10.1108/13598541211258609 Brandenburg, 2014, Quantitative models for sustainable supply chain management: developments and directions, Eur. J. Oper. Res., 233, 299, 10.1016/j.ejor.2013.09.032 Kochan, 2018, Supply chain resilience: a systematic literature review and typological framework, Int. J. Phys. Distrib. Logist. Manag., 48, 842, 10.1108/IJPDLM-02-2017-0099 Parejo, 2012, Metaheuristic optimization frameworks: a survey and benchmarking, Soft Comput, 16, 527, 10.1007/s00500-011-0754-8 Saunders, 2016 Gupta, 1999, A hierarchical Lagrangean relaxation procedure for solving midterm planning problems, Ind. Eng. Chem. Res., 38, 1937, 10.1021/ie980782t Gupta, 2003, Managing demand uncertainty in supply chain planning, Comput. Chem. Eng., 27, 1219, 10.1016/S0098-1354(03)00048-6 Min, 2002, Supply chain modeling: past, present and future, Comput. Ind. Eng., 43, 231, 10.1016/S0360-8352(02)00066-9 Huang, 2003, The impacts of sharing production information on supply chain dynamics: a review of the literature, Int. J. Prod. Res., 41, 1483, 10.1080/0020754031000069625 Ş.Y. Balaman, Basics of Decision-Making in Design and Management of Biomass-Based Production Chains. 2019. Gupta, 2005, The capacitated lot-sizing and scheduling problem with sequence-dependent setup costs and setup times, Comput. Oper. Res., 32, 727, 10.1016/j.cor.2003.08.014 Rasmi, 2019, A multi-criteria decision analysis to include environmental, social, and cultural issues in the sustainable aggregate production plans, Comput. Ind. Eng., 132, 348, 10.1016/j.cie.2019.04.036 Omar, 2007, Hierarchical production planning and scheduling in a multi-product, batch process environment, Int. J. Prod. Res., 45, 1029, 10.1080/00207540600724989 Xue, 2011, Integrated production planning with sequence-dependent family setup times, Int. J. Prod. Econ., 131, 674, 10.1016/j.ijpe.2011.02.012 Aghezzaf, 2011, A robust hierarchical production planning for a capacitated two-stage production system, Comput. Ind. Eng., 60, 361, 10.1016/j.cie.2010.12.005 Fumero, 2016, A multiproduct batch plant design model incorporating production planning and scheduling decisions under a multiperiod scenario, Appl. Math. Model., 40, 3498, 10.1016/j.apm.2015.09.046 Fumero, 2017, An MILP model for planning of batch plants operating in a campaign-mode, Ann. Oper. Res., 258, 415, 10.1007/s10479-016-2301-6 Wang, 2001, Aggregate production planning with multiple objectives in a fuzzy environment, Eur. J. Oper. Res., 133, 521, 10.1016/S0377-2217(00)00196-X Leung, 2009, A goal programming model for aggregate production planning with resource utilization constraint, Comput. Ind. Eng., 56, 1053, 10.1016/j.cie.2008.09.017 Baykasoglu, 2010, Multi-objective aggregate production planning with fuzzy parameters, Adv. Eng. Softw., 41, 1124, 10.1016/j.advengsoft.2010.07.002 Sillekens, 2011, Aggregate production planning in the automotive industry with special consideration of workforce flexibility, Int. J. Prod. Res., 49, 5055, 10.1080/00207543.2010.524261 Mirzapour Al-E-Hashem, 2011, A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty, Int. J. Prod. Econ., 134, 28, 10.1016/j.ijpe.2011.01.027 Zhang, 2012, The activity-based aggregate production planning with capacity expansion in manufacturing systems, Comput. Ind. Eng., 62, 491, 10.1016/j.cie.2011.10.016 Ramezanian, 2012, An aggregate production planning model for two phase production systems: solving with genetic algorithm and tabu search, Expert Syst. Appl., 39, 1256, 10.1016/j.eswa.2011.07.134 Chakrabortty, 2013, Solving an aggregate production planning problem by using multi-objective genetic algorithm (MOGA) approach, Int. J. Ind. Eng. Comput., 4, 1 Khalili-Damghani, 2014, Solving a new multi-period multi-objective multi-product aggregate production planning problem using fuzzy goal programming, Ind. Eng. Manag. Syst., 13, 369 Tavaghof-Gigloo, 2016, Mixed integer linear programming formulation for flexibility instruments in capacity planning problems, Comput. Ind. Eng., 97, 101, 10.1016/j.cie.2016.04.013 Gholamian, 2016, Multi-objective multi-product multi-site aggregate production planning in a supply chain under uncertainty: fuzzy multi-objective optimisation, Int. J. Comput. Integr. Manuf., 29, 149 de Kruijff, 2018, Integer programming models for mid-term production planning for high-tech low-volume supply chains, Eur. J. Oper. Res., 269, 984, 10.1016/j.ejor.2018.02.049 Mehdizadeh, 2018, A bi-objective aggregate production planning problem with learning effect and machine deterioration: modeling and solution, Comput. Oper. Res., 91, 21, 10.1016/j.cor.2017.11.001 Djordjevic, 2019, A fuzzy linear programming model for aggregated production planning (APP)in the automotive industry, Comput. Ind., 110, 48, 10.1016/j.compind.2019.05.004 Bensmain, 2019, Preventive remanufacturing planning of production equipment under operational and imperfect maintenance constraints: a hybrid genetic algorithm based approach, Reliab. Eng. Syst. Saf., 185, 546, 10.1016/j.ress.2018.09.001 Grabowski, 2004, A very fast tabu search algorithm for the permutation flow shop problem with makespan criterion, Comput. Oper. Res., 31, 1891, 10.1016/S0305-0548(03)00145-X Nonås, 2005, Optimal and heuristic solutions for a scheduling problem arising in a foundry, Comput. Oper. Res., 32, 2351, 10.1016/j.cor.2004.03.007 Bellabdaoui, 2006, A mixed-integer linear programming model for the continuous casting planning, Int. J. Prod. Econ., 104, 260, 10.1016/j.ijpe.2004.10.016 Hooker, 2007, Planning and Scheduling by Logic-Based Benders Decomposition, Oper. Res., 55, 588, 10.1287/opre.1060.0371 Doganis, 2007, Optimal scheduling in a yogurt production line based on mixed integer linear programming, J. Food Eng., 80, 445, 10.1016/j.jfoodeng.2006.04.062 Gaglioppa, 2008, Multitask and Multistage Production Planning and Scheduling for Process Industries, Oper. Res., 56, 1010, 10.1287/opre.1080.0525 Moon, 2008, Genetic algorithms for job shop scheduling problems with alternative routings, Int. J. Prod. Res., 46, 2695, 10.1080/00207540701244820 Doganis, 2008, Optimal production scheduling for the dairy industry, Ann. Oper. Res., 159, 315, 10.1007/s10479-007-0285-y Fakhrzad, 2009, Combination of genetic algorithm with Lagrange multipliers for lot-size determination in multi-stage production scheduling problems, Expert Syst. Appl., 36, 10180, 10.1016/j.eswa.2008.12.013 Mohammadi, 2012, A multi-objective optimisation model to integrating flexible process planning and scheduling based on hybrid multi-objective simulated annealing, Int. J. Prod. Res., 50, 5063, 10.1080/00207543.2011.631602 Guimarães, 2013, Pricing, relaxing and fixing under lot sizing and scheduling, Eur. J. Oper. Res., 230, 399, 10.1016/j.ejor.2013.04.030 Cheng, 2013, A genetic algorithm for the multi-stage and parallel-machine scheduling problem with job splitting-A case study for the solar cell industry, Int. J. Prod. Res., 51, 4755, 10.1080/00207543.2013.774468 Chen, 2013, A hybrid approach based on the variable neighborhood search and particle swarm optimization for parallel machine scheduling problems - A case study for solar cell industry, Int. J. Prod. Econ., 141, 66, 10.1016/j.ijpe.2012.06.013 Motta Toledo, 2014, A genetic algorithm/mathematical programming approach to solve a two-level soft drink production problem, Comput. Oper. Res., 48, 40, 10.1016/j.cor.2014.02.012 Na, 2014, Multi-level job scheduling in a flexible job shop environment, Int. J. Prod. Res., 52, 3877, 10.1080/00207543.2013.848487 Franz, 2014, Resequencing orders on mixed-model assembly lines: heuristic approaches to minimise the number of overload situations, Int. J. Prod. Res., 52, 5823, 10.1080/00207543.2014.918293 Mattik, 2014, Hierarchical scheduling of continuous casters and hot strip mills in the steel industry: a block planning application, Int. J. Prod. Res., 52, 2576, 10.1080/00207543.2013.860248 Golle, 2014, Car sequencing versus mixed-model sequencing: a computational study, Eur. J. Oper. Res., 237, 50, 10.1016/j.ejor.2014.01.012 Baumann, 2014, A hybrid method for large-scale short-term scheduling of make-and-pack production processes, Eur. J. Oper. Res., 236, 718, 10.1016/j.ejor.2013.12.040 Abdeljaouad, 2015, Job-shop production scheduling with reverse flows, Eur. J. Oper. Res., 244, 117, 10.1016/j.ejor.2015.01.013 Aroui, 2017, Minimising work overload in mixed-model assembly lines with different types of operators: a case study from the truck industry, Int. J. Prod. Res., 55, 6305, 10.1080/00207543.2017.1346313 Zeppetella, 2017, Optimal production scheduling with customer-driven demand substitution, Int. J. Prod. Res., 55, 1692, 10.1080/00207543.2016.1223895 Torkaman, 2018, Hybrid simulated annealing and genetic approach for solving a multi-stage production planning with sequence-dependent setups in a closed-loop supply chain, Appl. Soft Comput. J., 71, 1085, 10.1016/j.asoc.2017.10.019 Lopes, 2018, Balancing and cyclically sequencing synchronous, asynchronous, and hybrid unpaced assembly lines, Int. J. Prod. Econ., 203, 216, 10.1016/j.ijpe.2018.06.012 Bin Woo, 2018, Matheuristic approaches for parallel machine scheduling problem with time-dependent deterioration and multiple rate-modifying activities, Comput. Oper. Res., 95, 97, 10.1016/j.cor.2018.02.017 Verbiest, 2018, A matheuristic approach for the design of multiproduct batch plants with parallel production lines, Eur. J. Oper. Res., 273, 933, 10.1016/j.ejor.2018.09.012 Mönch, 2018, A matheuristic framework for batch machine scheduling problems with incompatible job families and regular sum objective, Appl. Soft Comput. J., 68, 835, 10.1016/j.asoc.2017.10.028 Ekici, 2019, An application of unrelated parallel machine scheduling with sequence-dependent setups at Vestel Electronics, Comput. Oper. Res., 111, 130, 10.1016/j.cor.2019.06.007 Chansombat, 2019, A mixed-integer linear programming model for integrated production and preventive maintenance scheduling in the capital goods industry, Int. J. Prod. Res., 57, 61, 10.1080/00207543.2018.1459923 de Armas, 2019, Parallel machine, capacitated lot-sizing and scheduling for the pipe-insulation industry, Int. J. Prod. Res. Wang, 2019, Two-stage hybrid flow shop batching and lot streaming with variable sublots and sequence-dependent setups, Int. J. Prod. Res., 57, 6893, 10.1080/00207543.2019.1571251 De Smet, 2020, A linearisation approach to the stochastic dynamic capacitated lotsizing problem with sequence-dependent changeovers, Int. J. Prod. Res., 58, 4980, 10.1080/00207543.2020.1736722 Yang, 2020, The distributed assembly permutation flowshop scheduling problem with flexible assembly and batch delivery, Int. J. Prod. Res., 0, 1 Otto, 2020, Product sequencing in multiple-piece-flow assembly lines, Omega (United Kingdom), 91 Rodoplu, 2020, A fix-and-relax heuristic for the single-item lot-sizing problem with a flow-shop system and energy constraints, Int. J. Prod. Res., 58, 6532, 10.1080/00207543.2019.1683249 Supply Chain Council SCC, Supply Chain Operations Reference Model SCOR version 11.0. 2012. Stoop, 1996, The complexity of scheduling in practice, Int. J. Oper. Prod. Manag., 16, 37, 10.1108/01443579610130682 Gelders, 1981, Production planning: a review, Eur. J. Oper. Res., 7, 101, 10.1016/0377-2217(81)90271-X Andres, 2018, Optimization Models to Support Decision-Making in Collaborative Networks: a Review, Closing the Gap Between Practice and Research in Industrial Engineering, 249, 10.1007/978-3-319-58409-6_28 A.C. Hax and H.C. Meal, “Hierarchical integration of production planning and scheduling,” 1973. Vieira, 2004, A new multi-objective optimization method for master production scheduling problems using simulated annealing, Int. J. Prod. Res., 42, 4609, 10.1080/00207540410001733869 Rodammer, 1988, A recent survey of production scheduling, IEEE transactions on systems, man, and cybernetics., 18, 841, 10.1109/21.23085 Thomas, 1993, An overview of production planning, Handbooks Oper. Res. Manag. Sci., 4, 333, 10.1016/S0927-0507(05)80187-2 Fang, 2017, A stochastic production planning problem in hybrid manufacturing and remanufacturing systems with resource capacity planning, J. Glob. Optim., 68, 851, 10.1007/s10898-017-0500-6 de A. Prata, 2020, Heuristic methods for the single-machine scheduling problem with periodical resource constraints, Top de A. Prata, 2020, Customer order scheduling problem to minimize makespan with sequence-dependent setup times, Comput. Ind. Eng. Kreipl, 2004, Planning and Scheduling in Supply Chains: an Overview of Issues in Practice, Prod. Oper. Manag., 13, 77, 10.1111/j.1937-5956.2004.tb00146.x Andres, 2016, A Cloud Platform to support Collaboration in Supply Networks, Int. J. Prod. Manag. Eng., 4, 5, 10.4995/ijpme.2016.4418 Gavrilas, 2010, Heuristic and metaheuristic optimization techniques with application to power systems, Int. Conf. Math. Methods Comput. Tech. Electr. Eng. - Proc., 95 Sörensen, 2018, A History of Metaheuristics, 1 Boschetti, 2009, Matheuristics: optimization, simulation and control, 171 Andreoni, 2014, Manufacturing Competitiveness in South Africa : matching industrial systems and policies, Int. Conf. Manuf. Led Growth Employ. Equal., 1 Chen, 2016, Industrial information integration—A literature review 2006–2015,”, J. Ind. Inf. Integr., 2, 30 Chen, 2020, A survey on industrial information integration 2016–2019, J. Ind. Integr. Manag., 5, 33, 10.1142/S2424862219500167 Andres, 2016, A decision support system for the collaborative selection of strategies in enterprise networks, Decis. Support Syst., 91, 113, 10.1016/j.dss.2016.08.005 Sahinidis, 2019, Mixed ‑ integer nonlinear programming 2018, Optim. Eng., 20, 301, 10.1007/s11081-019-09438-1 Kronqvist, 2019 Pellerin, 2020, A survey of hybrid metaheuristics for the resource-constrained project scheduling problem, Eur. J. Oper. Res., 280, 395, 10.1016/j.ejor.2019.01.063 Perumal, 2019, A matheuristic for the driver scheduling problem with staff cars, Eur. J. Oper. Res., 275, 280, 10.1016/j.ejor.2018.11.011 Guzman, 2019, A matheuristic approach for sourcing, production, and delivery plans optimization, 208 Hall, 2003, Supply Chain Scheduling: batching and Delivery, Oper. Res., 51, 566, 10.1287/opre.51.4.566.16106 Vargas, 2016, Inter-enterprise architecture as a tool to empower decision- making in hierarchical collaborative production planning, Data Knowl. Eng. j., 105, 5, 10.1016/j.datak.2015.10.002