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Abdullahi, B, Ibrahim, Y M, Ibrahim, A and Bala, K (2019) Development of e-tendering evaluation system for Nigerian public sector. Journal of Engineering, Design and Technology , 18(01), 122–49.

Acheamfour, V K, Kissi, E, Adjei-Kumi, T and Adinyira, E (2019) Review of empirical arguments on contractor pre-qualification criteria. Journal of Engineering, Design and Technology , 18(01), 70–83.

Adu, E T and Opawole, A (2019) Assessment of performance of teamwork in construction projects delivery in South-Southern Nigeria. Journal of Engineering, Design and Technology , 18(01), 230–50.

Dadzie, J, Runeson, G and Ding, G (2019) Assessing determinants of sustainable upgrade of existing buildings. Journal of Engineering, Design and Technology , 18(01), 270–92.

Hellas, M S, Chaib, R and Verzea, I (2019) Artificial intelligence treating the problem of uncertainty in quantitative risk analysis (QRA). Journal of Engineering, Design and Technology , 18(01), 40–54.

Hulio, Z H and Jiang, W (2019) An assessment of effects of non-stationary operational conditions on wind turbine under different wind scenario. Journal of Engineering, Design and Technology , 18(01), 102–21.

Ibn Majdoub Hassani, Z, El Barkany, A, Jabri, A, El Abbassi, I and Darcherif, A M (2019) Hybrid approach for solving the integrated planning and scheduling production problem. Journal of Engineering, Design and Technology , 18(01), 172–89.

  • Type: Journal Article
  • Keywords: Planning; Operational research; Modelling; Genetic algorithms; Optimization algorithms; Production; Scheduling; Mono criteria; Integrated approach; HSAGA; Simulated annealing;
  • ISBN/ISSN: 1726-0531
  • URL: https://doi.org/10.1108/JEDT-11-2018-0198
  • Abstract:
    This paper aims to present a new model for solving the integrated production planning and scheduling. Usually, the two decision levels are treated sequentially because of their complexity. Scheduling depends on the lot sizes calculated at the tactical level and ignoring scheduling constraints generates unrealistic and inconsistent decisions. Therefore, integrating more detail scheduling constraint in production planning is important for managing efficiently operations. Therefore, an integrated model was developed, and two evolutionary optimization approaches were suggested for solving it, namely, genetic algorithm (GA) and the hybridization of simulated annealing (SA) with GA HSAGA. The proposed algorithms have some parameters that must be adjusted using Taguchi method. Therefore, to evaluate the proposed algorithm, the authors compared the results given by GA and the hybridization. The SA-based local search is embedded into a GA search mechanism to move the GA away from being closed within local optima. The analysis shows that the combination of simulated annealing with GA gives better solutions and minimizes the total production costs. Design/methodology/approach The paper opted for an approached resolution method particularly GA and simulated annealing. The study represents a comparison between the results found using GA and the hybridization of simulated annealing and GA. A total of 45 instances were studied to evaluate job-shop problems of different sizes. Findings The results illustrate that for 36 instances of 45, the hybridization of simulated annealing and GA HSAGA has provided best production costs. The efficiency demonstrated by HSAGA approach is related to the combination between the exploration ability of GA and the capacity to escape local optimum of simulated annealing. Originality/value This study provides a new resolution approach to the integration of planning and scheduling while considering a new operational constrain. The model suggested aims to control the available capacity of the resources and guaranties that the resources to be consumed do not exceed the real availability to avoid the blocking that results from the unavailability of resources. Furthermore, to solve the MILP model, a GA is proposed and then it is combined to simulated annealing.

Luo, Z, Chen, Y, Cen, K, Pan, H, Zhong, M and He, J (2019) Research on comprehensive environmental impact assessment of shale gas development. Journal of Engineering, Design and Technology , 18(01), 1–20.

Mengistu, D G and Mahesh, G (2019) Dimensions for improvement of construction management practice in Ethiopian construction industry. Journal of Engineering, Design and Technology , 18(01), 21–39.

Neshat, N, Hadian, H and Rahimi Alangi, S (2019) Technological learning modelling towards sustainable energy planning. Journal of Engineering, Design and Technology , 18(01), 84–101.

Othman, A A E and Khalil, M H (2019) Divergent heritage sustainability: a threefold approach through lean talent management. Journal of Engineering, Design and Technology , 18(01), 150–71.

Patel, T D, Haupt, T C and Bhatt, T (2019) Fuzzy probabilistic approach for risk assessment of BOT toll roads in Indian context. Journal of Engineering, Design and Technology , 18(01), 251–69.

Soltani, M, Aouag, H and Mouss, M D (2019) An integrated framework using VSM, AHP and TOPSIS for simplifying the sustainability improvement process in a complex manufacturing process. Journal of Engineering, Design and Technology , 18(01), 211–29.

Syed Abu Bakar, S P, Jaafar, M and Muhibudin, M (2019) Intensifying business success of Malaysian housing development firms through entrepreneurial learning. Journal of Engineering, Design and Technology , 18(01), 190–210.

Yap, J B H and Toh, H M (2019) Investigating the principal factors impacting knowledge management implementation in construction organisations. Journal of Engineering, Design and Technology , 18(01), 55–69.