A Novel Collaborative Optimization Model for Job Shop Production–Delivery Considering Time Window and Carbon Emission

Abstract

The manufacturing industry is undergoing transformation and upgrading from traditional manufacturing to intelligent manufacturing, in which Internet of Things (IoT) technology plays a central role in promoting the development of intelligent manufacturing. In order to solve the problem that low production efficiency and machine utilization lead to serious pollution emissions in the workshop caused by untimely transmission of information in all links of the production and manufacturing process to whole supply chains, this study establishes an intelligent production scheduling and logistics delivery model with IoT technology to promote green and sustainable development of intelligent manufacturing. Firstly, an application framework of IoT technology in production–delivery supply chain systems was established to improve efficiency and achieve the integration of production and delivery. Secondly, an integrated production–delivery model was constructed, which takes into account time and low carbon constraints. Finally, a two-layer optimization algorithm was proposed to solve this integration problem. Through a case study, the results show this integration production–delivery model can reduce the cost of supply chains and improve customer satisfaction. Moreover, it proves that carbon emission cost is a major factor affecting total cost, and it could help enterprises to realize the profit and sustainable development of the environment. The production–delivery model could also support the last kilometer distribution problem and extension under E-commerce applications.

An optimization model with stochastic variables for flexible production logistics planning

“…The study applies a sequen-tial black hole-floral pollination heuristic algorithm for minimizing period deviance, energy consumption, route length, and emissions. [8] establish an intelligent production scheduling and logistics delivery model with IoT technology to promote green and sustainable development of manufacturing. The study proposes a two-layer optimization applying a genetic algorithm (GA) for minimizing operating costs and carbon emissions when scheduling a production and delivery process.…”

“…The order and time of visitation of every node is given by constraint (7), where M is a large enough number. Constraint (8) guarantees that the pickup node is visited before the delivery node, while (9) imposes the time windows for each node. Finally, constraint (10) set the feasible space for x.…”

Sustainability-Oriented Project Scheduling Based on Z-Fuzzy Numbers for Public Institutions

“…No relation to the three dimensions of sustainability (i.e., social sustainability, environment sustainability, economic sustainability) was given. Sustainable Job-Shop scheduling approaches were presented in [13,14], but the three dimensions of sustainability were not considered, either. In [13], authors considered energy efficiency, while in [14] carbon emission was considered.…”

“…Sustainable Job-Shop scheduling approaches were presented in [13,14], but the three dimensions of sustainability were not considered, either. In [13], authors considered energy efficiency, while in [14] carbon emission was considered. Similarly, reference [15] described sustainable production scheduling in the context of minimizing pollution.…”

Order Acceptance and Scheduling Problem with Carbon Emission Reduction and Electricity Tariffs on a Single Machine

“…Even though OAS problems have been studied extensively [7], prior OAS studied have not adopted the concept of green manufacturing that has received increasing attention among enterprises [22][23][24][25]. In particular, some recent works studied the carbon emission in the scheduling problems [26][27][28]. This paper focuses on the electricity power and excludes fuel consumption.…”