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The purpose of this paper is to propose a novel improved teaching and learning-based algorithm (TLBO) to enhance its convergence ability and solution accuracy, making it more suitable for solving large-scale optimization issues.

Utilizing multiple cooperation mechanisms in teaching and learning processes, an improved TBLO named CTLBO (collectivism teaching-learning-based optimization) is developed. This algorithm introduces a new preparation phase before the teaching and learning phases and applies multiple teacher–learner cooperation strategies in teaching and learning processes. Applying modularization idea, based on the configuration structure of operators of CTLBO, six variants of CTLBO are constructed. For identifying the best configuration, 30 general benchmark functions are tested. Then, three experiments using CEC2020 (2020 IEEE Conference on Evolutionary Computation)-constrained optimization problems are conducted to compare CTLBO with other algorithms. At last, a large-scale industrial engineering problem is taken as the application case.

Experiment with 30 general unconstrained benchmark functions indicates that CTLBO-c is the best configuration of all variants of CTLBO. Three experiments using CEC2020-constrained optimization problems show that CTLBO is one powerful algorithm for solving large-scale constrained optimization problems. The application case of industrial engineering problem shows that CTLBO and its variant CTLBO-c can effectively solve the large-scale real problem, while the accuracies of TLBO and other meta-heuristic algorithm are far lower than CLTBO and CTLBO-c, revealing that CTLBO and its variants can far outperform other algorithms. CTLBO is an excellent algorithm for solving large-scale complex optimization issues.

The innovation of this paper lies in the improvement strategies in changing the original TLBO with two-phase teaching–learning mechanism to a new algorithm CTLBO with three-phase multiple cooperation teaching–learning mechanism, self-learning mechanism in teaching and group teaching mechanism. CTLBO has important application value in solving large-scale optimization problems.

This paper is to explore how cross-functional integration (CFI) of production-marketing can impact the firm's build-to-order (BTO) competitiveness, marketing performance (MP) and financial performance (FP).

Empirical study with the structural equation modeling approach is applied. Six hypotheses are constructed and tested based on survey data collected from Chinese manufacturing firms.

The survey data supports that production-marketing integration (PMI) improves BTO competitiveness (BTOC) and MP and that BTOC also positively affects marketing outcome which, in turn, impacts a firm's FP. The results reveal that CFI of production-marketing is an effective approach for achieving the BTO manufacturing strategy and can improve organizational performance.

The paper uncovers the role of CFI of production-marketing in BTO manufacturing strategy and its impacts on a firm's MP and FP and provides important managerial implications for practitioners to improve organizational time-based competitiveness and performance in today's time-based competition era.

Equipment reliability significantly impacts productivity, and in order to obtain high equipment reliability and productivity, maintenance and production decision should be made simultaneously to keep manufacturing system healthy. The purpose of this paper is to investigate the joint optimization of equipment maintenance and production decision for k-out-of-n system equipment with attenuation of product quality and to explore the impact of maintenance on the production and cost control for manufacturers.

A multi-period Markov chain model for k-out-of-n system equipment is set up based on the assumption that the deterioration of equipment is a pure birth process. Then, the maintenance cost, setup cost, inventory holding cost, shortage cost, production cost and the quality cost are analyzed with the uncertain demand and the attenuation of product quality stemmed from equipment deterioration. The total lowest cost per unit time and its specific calculation method are presented. Finally, the robustness and flexibility of the method are verified by a numerical example and the effects of equipment deterioration intensity and attenuation of product quality are analyzed.

The result shows that the joint decision model could not only satisfy the uncertain demand with low cost and strong robustness but also make the output products high quality level. In addition, the attenuation of product quality would influence the equipment maintenance and production decision and leads to the production waste and increases the operation cost greatly.

Implications derived from this study can help production maintenance managers and reliability engineers adequately select maintenance policy to improve the equipment efficiency and productivity with high quality level at a relatively low cost.

The purpose of this paper is to investigate the behavioral operations effect in production inventory decision of supply chain consisting of one manufacturer and one buyer, and analyze how the unfairness concerns impact the decision of production inventory in a supply chain system.

First, a model without the buyer’s unfairness concern is established; then, advantage unfairness concern and disadvantage unfairness concern behavior of buyer are taken into account in the production inventory system. The authors analyze how advantage unfairness concern and disadvantage unfairness concern impact the optimal decisions and channel coordination.

The result shows several important conclusions. First, the buyer’s optimal ordering quantity and expected utility show opposing trend when the buyer has advantage unfairness concern. Second, the stronger bargaining power of the manufacturer results in an increasing buyer’s optimal ordering quantity under the advantage unfairness concern case, but decreasing under the disadvantage unfairness concern case. Third, the supply chain production-inventory can be coordinated under advantage unfairness concern case, but cannot be coordinated under disadvantage unfairness concern.

The study can provide to practitioners with important implications that when the vendor or the buyer in supply chain wants to make the decision of inventory replenishment, taking unfairness concerns into account will lead to different results. Therefore, to effectively improve the operations performance of supply chain, partners of the supply chain should not only care about their own interest, but also need to consider the fairness concern of the other partner, reflecting the cooperation consciousness of supply chain management.

This paper contributes to the new field of creative management–behavioral operations, offering managerial implications for the decision and optimization of supply chain production-inventory problem.

The purpose of this paper is to study a production lot sizing problem with consideration of imperfect manufacturing and emergency maintenance policy, providing managerial implication for practitioners.

In this study, the authors introduce two models, where in Model I, shortages are not allowed and repair times are negligible. In Model II, shortages are allowed and are partially backlogged, and repair times are assumed to be exponentially distributed, algorithm is developed to solve the models, numerical examples were demonstrated the applications.

Results show that in the Model I, demand rate is the most significant parameter affecting the average expected cost, whereas the time needed to breakdown after machine shift is the most significant factor affecting the production lot size. Therefore, reduction in the time needed to breakdown after machine shift would be helpful for determining an appropriate production lot size in Model I. In Model II, repair time parameter is the most significant factor affecting the average expected cost. Reducing the value of machine shift parameter would be helpful for determining an adequate production lot size and reducing decision risk.

This paper can provide important reference value for practitioners with managerial implication of how to effectively maintain equipment, i.e. how to make product lot size considering the influence of the maintenance policy.

From the aspect of academia, this paper provides a solution to the optimal production lot sizing decision for an imperfect manufacturing system with consideration of machine breakdown and emergency maintenance, which is a supplement to imperfect EMQ model.

The purpose of this paper is to examine the industrial production efficiency, pollution treatment efficiency, total factor energy efficiency and water efficiency in China with the consideration of technological innovation. This study also explores the distribution proportion of technological innovation between industrial production substage and pollution treatment substage.

A nonparametric method, data envelopment analysis (DEA), is used as the model foundation of this study. Specifically, a novel two-stage range-adjusted measure (RAM-DEA) with shared inputs is constructed to analyze the China’s industrial system. In this study, the panel data of 30 provinces from 2008 to 2015 are used.

This study found that although the current environmental regulation reduced the efficiency of industrial production, it could significantly improve the pollution treatment level. However, the lack of pollution treatment capacity was still an obstacle for development of China's industrial system. Compared with the total factor energy efficiency, the total factor water efficiency had more room for improvement. The optimal distribution of technological innovation in the two substages performed little change and the distribution roughly followed the “three-seven principle”.

More attention should be paid to improve the pollution treatment level and total factor water efficiency. And more R&D expenditure should be used in the industrial production substage in the eastern coastal areas, while in the inland areas, more R&D expenditure should be used in the pollution treatment substage.

This study proposed a model to environmental efficiency score with considering interval data under two-stage evaluation structure, which could strengthen the theory and expand the application scope of DEA approach.

The purpose of this paper is to investigate the relationships among just-in-time (JIT), total quality management (TQM) and production operations performance (POP) based on the survey data from Chinese manufacturing firms, provide managerial implications of effectively implementing JIT and TQM for firms in developing countries.

Questionnaires were collected from 173 Chinese manufacturing firms. Three hypotheses on the relationships among JIT, TQM and POP were first established based on literature review. Empirical study method of structural equation modeling using SPSS and AMOS as data processing tools is employed to test the hypotheses.

The results show that, on one hand, JIT positively influences TQM and POP; on the other hand, although TQM also has positive relationship with POP, the relationship is not significant at a given significant level. Meanwhile, the author survey also shows that JIT and TQM have complementary relationship, i.e., JIT and TQM can benefit each other in a firm.

TQM is a base of implementing JIT, it is valuable to concurrently implement JIT and TQM in manufacturing firms in order to improve the POP.

It is believed that this research reveals new insights about the JIT and TQM implementation in Chinese manufacturing firms; it has practice value for firms to improve the implementation performance of JIT and TQM.

The bottleneck of current DNA computing paradigms based on brute‐force search strategy is that initial solution space grows exponentially with problem size, thus only trivial instances of NP‐complete problem can be solved. The purpose of this paper is to present a novel molecular program based on sticker models for solving dominating set problems.

The authors do not synthesize the initial solution pool containing every possible candidate solution as previously reported algorithm. Instead, solutions DNA molecules to the problem of interest are constructed during the course of computation.

It is shown that “exponential explosions” inherent in current DNA computing paradigms may be overcome in this way.

The paper proposes an error‐resistant DNA algorithm based on sticker model for solving minimum dominating problems.

The purpose of this paper is to study the impact of learning effect and demand uncertainty on aggregate production planning (APP), provide practitioners with some important managerial implications for improving production planning and productivity.

Motivated by the background of one labour-intensive manufacturing firm – a mosquito expellant factory – an APP model considering workforce learning effect and demand uncertainty is established. Numerical example and comparison with other two models without considering learning and uncertainty of demand are conducted.

The result shows that taking into account the uncertain demand and learning effect can reduce total production cost and increase flexibility of APP.

Managerial implications are provided for practitioners with four propositions on improving workforce learning effect, i.e. emphasizing employee training, combing individual and organizational learning and reduction of forgetting effect.

This paper has practice value in improving APP in labor-intensive manufacturing.

The purpose of this paper is to study the information support technologies of integrated production planning control for OEM (original equipment manufacturer) driven networked manufacturing systems, and offer implications to firms for implementing networked manufacturing.

OEM driven networked manufacturing and its operations modes and support technologies are first discussed. Then, integration framework of production planning and control is proposed and relative technologies are discussed. Finally, a case of the application of information support technologies in networked manufacturing is illustrated.

Both theory analysis and case experience show that information integration and sharing are critical for effective operations of OEM driven networked manufacturing and an integrated production planning and control system can benefit firms for successfully operating a networked manufacturing system.

It is valuable to develop and apply integrated production planning and control systems in OEM driven networked manufacturing, Firms should pay more attention to information sharing and communication with partners and utilize advanced information technologies to synchronize the operations of partners.

Integration framework of production planning and control proposed in this paper has originality and the technology strategies are also practical. Managerial ideas, technology framework and application strategies of integrated production planning and control are helpful for firms to implement OEM driven networked manufacturing.