A matheuristic approach for the design of multiproduct batch plants with parallel production lines

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

“…In this problem, the authors were able to obtain N-OP solutions and suggested researching other matheuristics with other types of combinations to improve the computation time of the algorithms they presented. Verbiest et al [73] described an MTA made up of an MILP model with an iterative local search algorithm for multiproduct batch plant designs on parallel production lines. With this combination they obtained good results in acceptable times, but proposed furthering their research to extend problems with more restrictions.…”

“…Although these studies were validated in a specific industry type, the proposed techniques and approaches could be applied to other sectors. In this category, several works conducted tests with similar data or instances to those of a real case [30,40,43,50,58,73].…”

“…Na & Park [62] x x S-M Khalili-Damghani & Shahrokh [41] x S Baumann & Trautmann [66] x x M-L Golle et al [65] Abdeljaouad et al [67] x x x S M-L x x x S M-L Gholamian et al [43] x M Tavaghof-Gigloo et al [42] x M Makui et al [1] x M Fumero et al [31] x S Aroui et al [68] x x S L Fang et al [91] x x S-M Fumero et al [32] x S Zeppetella et al [69] x S de Kruijff et al [44] x M Torkaman et al [70] x x S-M Mehdizadeh et al [45] x x S M Mönch & Roob [74] x x S L Verbiest et al [73] x x x S M-L Woo & Kim [72] x x x S-M L Lopes et al [71] x M Ekici et al [75] x L de Armas & Laguna [77] x M Chansombat et al [76] x x x S-M-L Djordjevic et al [46] x S Bensmain et al [47] x x x S M-L S. Wang et al [78] x x S-M De Smet et al [79] x…”

Matheuristic Algorithm for Job-Shop Scheduling Problem Using a Disjunctive Mathematical Model

“…In other production fields, matheuristics have obtained good solutions. The research of Cabrera-Guerrero et al [27] demonstrates that the combination of techniques, or hybridization, can be advantageous for solving complex problems, which is also demonstrated in [28]. Verbiest et al [28] used a combination of an iterated local search algorithm (metaheuristics) with an MILP model to optimize production lines, design installed lines and allocate products.…”

“…The research of Cabrera-Guerrero et al [27] demonstrates that the combination of techniques, or hybridization, can be advantageous for solving complex problems, which is also demonstrated in [28]. Verbiest et al [28] used a combination of an iterated local search algorithm (metaheuristics) with an MILP model to optimize production lines, design installed lines and allocate products. Their study compares the matheuristic approach with an exact method (MILP) to verify that the matheuristic offers efficient solutions and in a shorter calculation time.…”