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Production systems are stopped due to malfunctions such as rotting equipment, imbalance of rotating parts, and high vibration, which leads to loss of customers, reduction of market share and unemployment of personnel. In this research, using the absorbing Markov process, a mathematical model is formulated to analyze the maintenance policy of the production process, through which one of the four states of new, old, or failure due to deterioration or sudden failure can be allocated to the machine. It is assumed that the machine changes from one state to another with different probabilities, which are determined using a discrete Markov chain. The different maintenance policies can be analyzed to minimize the average production cost. The mathematical model is obtained using discrete Markov chain equations, and the optimal maintenance and repair policy can be analyzed by considering all types of costs, including maintenance, production, and failure costs, so that the average cost of the production process can be minimized. [ABSTRACT FROM AUTHOR]

This paper presents a model that examines sports teams' strategic choices about the extent of offense/defense to adopt in competing with other teams. The mathematical formulation adopted permits the derivation of a team's optimal strategy under different game scenarios (current score and time left to play), and team characteristics (playing at home or away, and each team's quality). A novel feature of the model is that teams can choose a strategy at several moments in the game, thereby incorporating a comprehensive dynamic element. The National Hockey League is used as an application. Optimal coaching behavior is derived in this setting, and the impact of rule changes is assessed. The study found that removing the overtime period, disproportionally increasing the rewards for a win, or removing the point that is currently awarded to the team that loses the shootout at the end of overtime, would all lead to the adoption of more offensive strategies during the game. That outcome is aligned with higher fan interest and team revenue. [ABSTRACT FROM AUTHOR]

This paper researches the impact of different innovation investment modes on the closed-loop supply chain (CLSC) profit and pricing decisions under an uncertain recycling quality background. Furthermore, we construct a battery swapping CLSC under three innovation investment modes. The research results show that: (1) Under the cooperative innovation investment mode, the decision variables and CLSC system profit all reach the optimal level. (2) Increasing the subscription duration can promote the reduction of subscription price, which is beneficial to the improvement of innovation investment level. (3) When the innovation cooperation coefficient is within a certain range, it will promote the increase of profits for the CLSC. (4) The balanced battery ratio is an important factor affecting enterprise decision-making, and it has a more significant impact on the battery swapping operator. (5) The power battery manufacturer can dynamically adjust the echelon utilization quality threshold according to the echelon utilization value to achieve optimal profit. [ABSTRACT FROM AUTHOR]

This paper delves into optimizing the rotation of relief supplies within the relief supply chain system, concentrating on reserve quantity decisions for governments and humanitarian organizations involved in disaster response. By integrating a trade-in strategy with suppliers, it ensures a precise and timely response to the fluctuating demand for relief supplies post-disaster. Utilizing the newsvendor model, optimization theory, and supply chain coordination principles, we developed a comprehensive model that calculates optimal reserve quantities for pre-positioning demanders. It also outlines the expected profit function for suppliers and a robust supply chain coordination model. The findings highlight that optimal stockpiling decisions for relief supplies are heavily influenced by cost parameters, material characteristics, and the relationship between trade-in pricing and market resale values. Notably, higher trade-in prices generally reduce the government's optimal reserve quantities, impacting strategic decisions within supply chain coordination. This research adds to disaster management literature by offering strategic insights into how coordination and pricing strategies can improve disaster preparedness and response efficiency and effectiveness. [ABSTRACT FROM AUTHOR]

Cold standby redundant structures can improve system reliability and availability but are subjected to internal degradation and external shocks during operation. Thus, the switching process in a standby system is prone to failures. This study investigates the optimal switching and condition-based maintenance (CBM) decision of a two-unit cold standby system subject to mutually dependent competitive failure processes with an imperfect switchover. First, periodic switching and offline CBM policies under imperfect switchover are proposed; second, the reliability models of competitive failure—between soft failure caused by system degradation subject to nonfatal shock and hard failure caused by fatal shock—are established. An iterative model of the system state probability distribution is subsequently derived by analysing the characteristics of state transitions in alternate use and maintenance of the active and standby units. An analytical decision model is also established to minimise the average cost rate in a finite horizon to obtain the optimal switching period and maintenance threshold. Finally, a case study of a coal mine main ventilator system validates the proposed model. [ABSTRACT FROM AUTHOR]

A novel robust controller is designed for Electric Helicopter Tail Deceleration (EHTD) system which is subject to uncertainties and nonlinearity. Then, the optimal parameters of the control are solved based on Stackelberg game theory. The fuzzy set theory is used to describe the uncertainty bound, which is distinguished from probability theory or fuzzy logic theory. Based on two-player (leader and follower) Stackelberg game, two performance indexes are proposed for novel robust controller which contains two optimal parameters. The system performance and control cost are included in performance indexes. Then, based on Stackelberg strategy, the optimal decisions are made by leader and follower, which can minimize the performance indexes. Therefore, by numerical simulation, the EHTD system is applied to prove that the design of robust control and optimal parameters based Stackelberg strategy are effective. • A novel robust controller is designed for Electric Helicopter Tail Deceleration system which is subject to uncertainties. • The novel robust controller contains two adjustable control parameters. • Based on Stackelberg game theory, the optimal decision can be chosen by players (leader and follower). [ABSTRACT FROM AUTHOR]

This paper delves into optimizing the rotation of relief supplies within the relief supply chain system, concentrating on reserve quantity decisions for governments and humanitarian organizations involved in disaster response. By integrating a trade-in strategy with suppliers, it ensures a precise and timely response to the fluctuating demand for relief supplies post-disaster. Utilizing the newsvendor model, optimization theory, and supply chain coordination principles, we developed a comprehensive model that calculates optimal reserve quantities for pre-positioning demanders. It also outlines the expected profit function for suppliers and a robust supply chain coordination model. The findings highlight that optimal stockpiling decisions for relief supplies are heavily influenced by cost parameters, material characteristics, and the relationship between trade-in pricing and market resale values. Notably, higher trade-in prices generally reduce the government’s optimal reserve quantities, impacting strategic decisions within supply chain coordination. This research adds to disaster management literature by offering strategic insights into how coordination and pricing strategies can improve disaster preparedness and response efficiency and effectiveness.

Maritime transportation is a crucial component of international cargo transport, offering several advantages, such as route flexibility, large capacity, and cost-effectiveness. The competition and collaboration among the node enterprises in the sea-cargo supply chain system (SCSCS) directly impact the overall structure and efficiency of the supply chain system, introducing complexity in analysis. This research focuses on a two-level SCSCS comprising one shipping company and two competing freight forwarders, considering their altruistic preferences manifested through contributing to the shipping company's brand building. Employing a Stackelberg game model, this study examines the effects of the shipping company's brand investment willingness and the freight forwarders' altruistic preferences on the decision making and profits of all stakeholders. The findings reveal that a higher willingness of the shipping company to invest in its brand building leads to increased profits for all parties involved. However, while the altruistic behaviors of the freight forwarders can enhance the shipping company's profits, their own profits may not necessarily see the same impact. Furthermore, moderate competition between the freight forwarders can enhance the profits for all members. This research identifies the circumstances in which the freight forwarders' altruistic preferences can lead to increased profits for themselves, achieving both altruistic and self-interested outcomes. [ABSTRACT FROM AUTHOR]

This study investigates the impacts of fairness concerns on a two-tier green agricultural product supply chain (GAPSC) with an agricultural cooperative making green input and a retailer making fresh-keeping input. Game models are constructed and compared in four scenarios: centralized decision-making, decentralized decision-making without fairness concerns, and decentralized decision-making with the retailer considering or not considering the agricultural cooperative's fairness concerns. The results showed that fairness concerns will negatively impact the GAPSC. Agricultural cooperatives can make fairness concerns as appropriate. It is more beneficial for retailers to consider fairness concerns of agricultural cooperatives. The GAPSC operates most efficiently under centralized decision-making. [ABSTRACT FROM AUTHOR]

This study considers a supply chain consisting of a commodity supplier and a final product manufacturer with uncertain demand. In addition to purchasing from the supplier through a forward contract, the manufacturer can adjust their inventory by trading the commodity in an online spot market after observing the actual demand. However, the spot market is imperfect in that transactions cannot be certainly realized and come with additional transaction costs. Furthermore, the spot price is volatile such that overly relying on the spot market is unwise. To investigate how the spot market affects the decisions and coordination in a supply chain, we develop a game-theoretical model incorporating spot trading. We derive the optimal ordering decision in a centralized supply chain, as well as the supplier's and manufacturer's equilibrium pricing and ordering decisions in a decentralized supply chain. The impact of the imperfect spot market on the optimal decisions and profits is analyzed. This study also demonstrates how the supply chain can be coordinated in the presence of an imperfect spot market. Finally, a numerical analysis is performed to examine the analytical results. Our results indicate that the spot market can generally improve the performance of the centralized supply chain and benefit the manufacturer in the decentralized one. However, it can be detrimental to the supplier. The supply chain can be coordinated by a revenue-sharing contract, and both parties' profits can be improved. Our findings suggest that the manufacturer could take advantage of the spot market, and the supplier should attempt to integrate or coordinate the supply chain to share the benefits of spot trading.

Forest carbon sinks integrated into the carbon trading is an important way to solve the funding shortage of carbon emission reduction and is a major measure to achieve carbon sequestration and thereby carbon neutrality. We propose a carbon credit trading mechanism based on forest carbon sinks and build an optimal carbon credit trading model on forest companies and manufacturers. The scale of carbon sink forest and trading price is determined by stochastic differential game method. Reasonable emission reduction responsibilities are set to achieve coordination between forest carbon sequestration and economic development. The results show that farsighted forest company is more likely to participate in carbon credit trade when the total amount of forest carbon sequestration is small, while shortsighted forest company is more likely to participate in carbon credit trade when the total amount of forest carbon sequestration is large. Low emission reduction responsibility in carbon credit trade is conductive to increasing forest carbon sequestration, and improving the enthusiasm of shortsighted forest company to participate in the trade, which reflects the superiority of the proposed carbon credit trading mechanism. This implies that the forest company should undertake low emission reduction responsibilities to achieve a win–win situation for economic and environmental benefits. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Against the background of the COVID-19, cross-border e-commerce has further become an important channel for trade market development. The supply chain composed of an export retailer, a cross-border e-commerce platform and foreign consumers is studied. When the government gives or does not give subsidies to the platform, three cooperation modes between the platform and the export retailer are considered, that is, non cooperation mode, cost sharing mode and fixed cost mode. A Stackelberg game model among the export retailer, the platform and the government is established, and the decision-making results under each mode are analyzed and compared. The results show that whether the government provides subsidies for platforms has an important impact on the choice of cooperation modes between platforms and retailers. When the cost coefficient of platform promotion is large, the government should provide subsidies to the platform. When the government provides subsidies to platforms, cross-border e-commerce platforms and export retailers are more inclined to choose the non cooperative mode. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Decision making is one of the core problems of computational intelligence. Based on the theory of fuzzy mathematics, a general fuzzy decision tree model is established. The nodes are used to describe the decision premise and control information, and the edges of the tree are used to formalize the reasoning rules. The reasonable fuzzy decision operators are defined on the nodes and the edges to make a multi-level comprehensive decision. Engineering decisions consider the costs, feasibility, and benefits of different options. The fusion of these information is used to measure the merits and demerits of decision making schemes. The weighted fuzzy intelligent decision-making model is established, and the algorithm of multi-attribute constrained decision-making based on the model is given. The complexity of the model and algorithm is discussed. Finally, through two application examples, it is proven that the decision model and the algorithm of optimal decision scheme consider qualitative and quantitative information, and the decision result is scientific and reasonable with large amount of information.

With the development of commodity market, corporate social responsibility (CSR) has become a topic of widespread concern for both enterprises and society. Cause-related marketing (CRM), as an effective marketing tool for enterprises to fulfill their social responsibility, is rapidly being applied to all stages of the supply chain. However, there is no conclusive evidence on the implementation strategy of CRM for supply chain members. In this paper, we study the decision and pricing strategies of CRM for the manufacturer and the retailer by constructing models for two scenarios: the manufacturer implements CRM, and the retailer implements CRM. We conclude that the donation percentage and the pro-sociality of consumers have a significant impact on the strategic and pricing decisions for supply chain members. The wholesale and selling prices will be higher when the manufacturer implements CRM. Our result also shows that the manufacturer and retailer are profitable in CRM only when the donation amount exceeds a certain percentage. In addition, to maximize profits, the manufacturer is more likely to allow a retailer to implement CRM, and the retailer is only optimally positioned to implement CRM when the pro-sociality of consumers is high or when the donation percentage is high. [ABSTRACT FROM AUTHOR]

Deciding on a fuzzy environment faces many difficulties due to the lack of accuracy in data or permanently changing data. Fuzzy linear programming is one of the best methods used in a fuzzy environment which has a big role in making the right decision to solve a problem. This paper aims to identify the method of Fuzzy Linear Programming (FLP) to take the optimal decision and reach the optimal production for crude oil products of the North Refineries Company, This paper constructs the FLP model and solves the model to reach a production decision that contributes to maximizing profit and solves the model by using the methods of FLP. The fuzziness was removed from the model by using five methods. Comparison between the methods of removing fuzzy in a linear programming model to get maximum profit. The paper results that the highest maximum profit is (993423791) million dinars when using the bounded and decomposition method for the linear programming problem, which is higher than the profits achieved by the research company by (50%). The results were implemented by the software package python 3.9.

Maritime transportation is a crucial component of international cargo transport, offering several advantages, such as route flexibility, large capacity, and cost-effectiveness. The competition and collaboration among the node enterprises in the sea-cargo supply chain system (SCSCS) directly impact the overall structure and efficiency of the supply chain system, introducing complexity in analysis. This research focuses on a two-level SCSCS comprising one shipping company and two competing freight forwarders, considering their altruistic preferences manifested through contributing to the shipping company’s brand building. Employing a Stackelberg game model, this study examines the effects of the shipping company’s brand investment willingness and the freight forwarders’ altruistic preferences on the decision making and profits of all stakeholders. The findings reveal that a higher willingness of the shipping company to invest in its brand building leads to increased profits for all parties involved. However, while the altruistic behaviors of the freight forwarders can enhance the shipping company’s profits, their own profits may not necessarily see the same impact. Furthermore, moderate competition between the freight forwarders can enhance the profits for all members. This research identifies the circumstances in which the freight forwarders’ altruistic preferences can lead to increased profits for themselves, achieving both altruistic and self-interested outcomes.

Bank and e-commerce financing strategies are the main ways for farmers to solve the problem of capital shortage. Aiming at the uncertainty risk of the output of the agricultural product supply chain, we consider the risk attitudes of farmers; construct the Stackelberg game model under different financing strategies to obtain the optimal decision of e-commerce and farmers; and explore the expected output factors, the degree of farmers' risk aversion, e-commerce's interest rates on the decision-making results. Our research found that farmers with low-risk aversion prefer to choose the e-commerce financing strategy when the e-commerce's interest rates are lower. In addition, farmers' risk-averse attitudes lead to lower equilibrium decision-making between farmers and e-entrepreneurs, which is not conducive to the interests of e-commerce and farmers. A higher expected output factor reduces farmers' production inputs and e-commerce purchase price. When the expected output factor is low, the decision of whether e-commerce provides financing services to farmers is only affected by interest rates, and lower interest rates create more value for e-commerce. [ABSTRACT FROM AUTHOR]

This study examines the effect of the extended producer responsibility (EPR) coefficient policy on the production decision between a supplier and a manufacturer in a precious metal accessory recycling supply chain. EPR coefficient is a regulation proposed by the government and enterprises to balance economic profit and EPR behaviour, and refers to the production proportion of recycled products in all serviceable products. Enterprises with a large EPR coefficient have good EPR practice. This study uses the newsvendor model and numerical simulation to study a supply chain system with remanufacturing and reproduction processes. Results show that the optimal recycling mode and the optimal EPR coefficient are always present in precious metal accessory operations. The increasing market demand for recycled products and the improving whole recycling parameters are both effective in enlarging the optimal EPR coefficient. However, the improvement of single or partial recycling parameters (except the market demand parameter) has no effect on the optimal EPR coefficient. The implementation mechanism and applicable conditions of the EPR coefficient policy are also explored. This study indicates that the EPR coefficient policy is an appropriate and effective approach to promote the EPR practice of the Chinese Government. [ABSTRACT FROM AUTHOR]

Carbon cap-and-trade policy based on market mechanism becomes an important means to restrain shipping logistics enterprises' carbon emission reduction. This paper studies the new requirements of shipping enterprises under the pressure of carbon emission reduction. Considering the logistics service supply chain composed of two competing providers and one integrator under the constraint of carbon cap-and-trade policy, this paper explores the optimal pricing and revenue decision of shipping logistics service supply chain through vertical cooperation, horizontal cooperation between providers and revenue sharing cooperation among integrators. This paper obtains feedback strategies under different cooperation modes by constructing a game model. In the vertical game, the shipping logistics supplier is the Stackelberg leader, and the shipping logistics integrator is the follower; there is a Nash equilibrium in the emission reduction decisions among suppliers in the horizontal game. On this basis, the results of different cooperation modes are compared, and the influence of competitive strategies on the optimal results is discussed. We found that the vertical cooperation of the shipping logistics service supply chain has a higher carbon emission reduction rate and a lower sales price, and the horizontal cooperation of shipping logistics suppliers can improve their own profits but reduce the income of the shipping logistics integrators and consumer welfare. When the revenue sharing contract provides the shipping logistics integrator with a share proportion in a certain range, the revenue sharing contract can generate higher supply chain profits than the integration of two chains, which can urge shipping logistics suppliers to forfeit the horizontal cooperation and help the shipping logistics service supply chain achieve win-win results. [ABSTRACT FROM AUTHOR]

Understanding the trade-offs associated with the two operation stages of hydropower generation is critical for guiding efficient reservoir operations. Previous studies showed that the marginal return in Stage 2 is always higher than the marginal cost in Stage 1 if variations in tailwater levels are ignored. However, the tailwater level often raises faster than the reservoir water level, and thus reduces the net hydraulic head of the reservoirs with reaction turbines, especially in large-scale and low-head reservoirs. Therefore, this study considers the variations in tailwater levels and theoretically evaluates the marginal utility of the total power generation (TPG) in the two stages. It is found that the variation of TPG presents diminishing marginal utility and is closely related to the topography characteristics of the reservoir and downstream channels, as well as the relationship between releases in the two stages. The marginal return in Stage 2 might be lower than the marginal cost in Stage 1 when the release in Stage 2 exceeds that in Stage 1 for the reservoirs in which the tailwater level is sensitive to discharge and hydraulic head. This suggests that the carryover storage equalizing the marginal utility in the two stages is optimal, i.e., satisfying the marginal utility principle. Otherwise, the marginal return is always higher than the marginal cost, which suggests that as much carryover storage as possible should be saved. Following these findings, the reservoir states, represented by the storage difference and the total inflow in the two stages, that satisfy the marginal utility principle are identified. Further, the optimal carryover storage under different levels of inflow and storage difference is derived. The theoretical findings are verified with four hydropower plants in China. Results confirm the theoretical findings and show that two-stage hydropower generation coupled with operating rules can greatly improve the performance of hydropower generation. [ABSTRACT FROM AUTHOR]

In a multi-agent system, the complex interaction among agents is one of the difficulties in making the optimal decision. This paper proposes a new action value function and a learning mechanism based on the optimal equivalent action of the neighborhood (OEAN) of a multi-agent system, in order to obtain the optimal decision from the agents. In the new Q-value function, the OEAN is used to depict the equivalent interaction between the current agent and the others. To deal with the non-stationary environment when agents act, the OEAN of the current agent is inferred simultaneously by the maximum a posteriori based on the hidden Markov random field model. The convergence property of the proposed methodology proved that the Q-value function can approach the global Nash equilibrium value using the iteration mechanism. The effectiveness of the method is verified by the case study of the top-coal caving. The experiment results show that the OEAN can reduce the complexity of the agents' interaction description, meanwhile, the top-coal caving performance can be improved significantly. [ABSTRACT FROM AUTHOR]

Edge computing is a promising alternative to cloud computing for offloading computationally heavy tasks from resource-constrained mobile user devices. Placed at the edge of the network, edge computing is particularly advantageous to delay-limited applications for having a short distance to end-users. However, when a mobile user moves away from the service coverage of the associated edge server, the advantage gradually vanishes, increasing response time. Although service migration has been studied to address this problem focusing on minimizing the service downtime, both zero-downtime and the amount of traffic generated as a result of migration need further study. In this paper, an optimal live migration for containerized edge computing service is studied. This paper presents three zero-downtime migration techniques based on state duplication and state reproduction techniques, and then, proposes an optimal migration technique selection algorithm that jointly minimizes the response time and network traffic during migration. For validation and performance comparison, the proposed migration techniques are implemented on off-the-shelf hardware with Linux operating system. The evaluation results showed that compared with a naive migration, the optimal approach reduced the response time and network load by at least 74.75% and 94.79%, respectively, under considered scenarios.

The main goal of this work is to propose two new Bayesian approaches to equivalence tests for two binomial proportions. As a result, we prove that these Bayesian hypothesis tests are equivalent. In this way, aiming to improve the safety of clinical trials, we use optimal decision rules to minimize the linear combination of the type I and type II error probabilities. Moreover, a significance level that is a function of the sample size is used. These Bayesian methodologies overcome some limitations of the frequentist approach predominantly used for these equivalence tests. A simulation study was carried out to assess the rate of the type I error probability and the power of the tests under different scenarios. We present a table for determining the optimal sample size in a practical way. The methodologies are illustrated with a data set on acute maxillary sinusitis. [ABSTRACT FROM AUTHOR]

In construction projects, owners' and contractors' decisions as to whether or not share their tacit knowledge transparently with each other determines the choice of project delivery and contracting methods and their collaborative behaviors in the projects. The dynamic of collaboration is a complex one and is often influenced by the other player's intent to collaborate. This paper proposes a quantitative framework using game theory to analyze the collaborative dynamic interplay in construction projects. The framework demonstrates that when an owner's and a contractor's knowledge leveragability (L) is very high and synergy (S) is enhanced as a result of knowledge sharing in complex construction projects, the Nash equilibrium state lies beneath the Pareto frontier. This means that sharing tacit knowledge transparently about budgets by choosing the best value procurement with GMP or IPD contracts can promote collaboration and provide better payoffs to both stakeholders than not sharing the knowledge by choosing the Design–Bid–Build method using a low-bid procurement in conjunction with a fixed-price contract. This research contributes to the body of knowledge by proposing a theoretical framework that enables both owners and contractors to understand the economics of collaboration in the context of complex projects. [ABSTRACT FROM AUTHOR]

Applying model-based learning for the optimal decision of the multi-agent system is not trivial due to the expensive price or even the impossibility of obtaining the ground truth for training the model of the complex environment. Such as learning the optimal action of hydraulic supports in the top-coal caving, the optimal action could not accessible as the ground truth of the corresponding state in the intricate processes. Regarding the latent ground truth as the hidden variable is an effective method in the hidden Markov model. This paper extends the hidden variable of ground truth to the multi-agent system and proposes the hidden Markov random field (HMRF) model with reinforcement learning for optimizing the action decision of the multi-agent. In the HMRF model, the input states and the output actions of the multi-agent are considered as an observable random field and a latent Markov random field, respectively. Based on the HMRF model, the optimal decision is inferred by the maximum posterior probability with the prior probability obtained by Q-learning. Meanwhile, the parameters of the HMRF model are estimated by the expectation maximum algorithm. In the experiment, the top-coal caving demonstrates the effectiveness of the proposed method that the recall of top-coal is improved prominently with a very small price of increasing the rock-rate. Furthermore, the proposed method is employed to deal with the predator-preys problem in the gym. The experiment result shows that the communication between agents by the HMRF increases the reward of the preys.

Greenhouse gas emissions have gradually became an important problem hindering the sustainable development of human beings. This paper considers the carbon emissions generated by the manufacturer during the product warranty process. The impacts of cap-and-trade regulation on product warranty policy and carbon emission reduction strategy are studied. According to Stackelberg theory, two supply chain game models are established. In Model I, market demand only depends on the selling price and warranty period of the product. In Model II, the carbon emission reduction level of the product is also considered as a new important factor affecting market demand. The optimal decisions of Model I and Model II in the centralized and decentralized game structure are solved and a revenue-sharing contract is proposed to coordinate the low-carbon supply chain. According to theory analysis, the following conclusions are obtained: (1) Compared with Model I, the key decisions in Model II have better response. (2) Under all game structures, the products in the centralized scheme have higher carbon emission reduction levels and warranty periods. (3) The unit carbon trading price has a negative correlation with the carbon emission reduction level and warranty period of the product. Eventually, through a set of numerical experiments, the validity of the proposed contract is verified and sensitivity analysis on key parameters of the optimal strategies of the two models under different game policies is performed. [ABSTRACT FROM AUTHOR]

This study considers a manufacturer with ambidextrous sustainable innovation capability selling products in environmentally conscious market through an independent retailer in a two‐period game setting. We design a two‐period game theoretic and dyadic supply chain (SC) model considering exploitative and exploratory nature of environmental innovations. We study five different contract types, namely, wholesale price contract, vertical Nash game structure, cost sharing contract, revenue sharing contract and two‐part tariff contract. We demonstrate the impact of market sensitivity towards sustainable innovation and cost parameters on optimal level of decision parameters. The equilibrium results reveal that a suitably designed two‐part tariff contract can be used to achieve coordination in a fragmented SC. The equilibrium results assist managers to optimise the SC based on the two‐period contract model. The results obtained in this study can help the decision‐makers to take decisions on investment in the ambidextrous sustainable innovation under different types of contract structures. [ABSTRACT FROM AUTHOR]

Aiming at the fuzzy and uncertain problems in the decision-making process of the deep foundation pit support scheme, a deep foundation pit support scheme decision-making method based on the AHP-game weighting and VIKOR theory is proposed. The Analytic Hierarchy Process (AHP) is used to analyze the relative importance of each evaluation index that determines the subjective weight in the decision-making system of the deep foundation pit support scheme. The improved entropy weight theory is used to calculate the information entropy and the difference coefficient of the evaluation index that determines the objective weight of the evaluation index. And the linear combination coefficient is used to obtain the optimal combination weight. Finally, the VIKOR theory is used to determine the overall utility value and individual regret value of each scheme, and the deep foundation pit support scheme with the largest comprehensive benefit is obtained in a compromise way. The demonstration of a deep foundation pit project shows that the method is easy to be operated and calculated, and has strong practicability. This provides a reliable basis for the decision-making of the deep foundation pit support schemes. [ABSTRACT FROM AUTHOR]

In a multi-agent system, the complex interaction among agents is one of the difficulties in making the optimal decision. This paper proposes a new action value function and a learning mechanism based on the optimal equivalent action of the neighborhood (OEAN) of a multi-agent system, in order to obtain the optimal decision from the agents. In the new Q-value function, the OEAN is used to depict the equivalent interaction between the current agent and the others. To deal with the non-stationary environment when agents act, the OEAN of the current agent is inferred simultaneously by the maximum a posteriori based on the hidden Markov random field model. The convergence property of the proposed methodology proved that the Q-value function can approach the global Nash equilibrium value using the iteration mechanism. The effectiveness of the method is verified by the case study of the top-coal caving. The experiment results show that the OEAN can reduce the complexity of the agents’ interaction description, meanwhile, the top-coal caving performance can be improved significantly.

In construction projects, owners’ and contractors’ decisions as to whether or not share their tacit knowledge transparently with each other determines the choice of project delivery and contracting methods and their collaborative behaviors in the projects. The dynamic of collaboration is a complex one and is often influenced by the other player’s intent to collaborate. This paper proposes a quantitative framework using game theory to analyze the collaborative dynamic interplay in construction projects. The framework demonstrates that when an owner’s and a contractor’s knowledge leveragability (L) is very high and synergy (S) is enhanced as a result of knowledge sharing in complex construction projects, the Nash equilibrium state lies beneath the Pareto frontier. This means that sharing tacit knowledge transparently about budgets by choosing the best value procurement with GMP or IPD contracts can promote collaboration and provide better payoffs to both stakeholders than not sharing the knowledge by choosing the Design–Bid–Build method using a low-bid procurement in conjunction with a fixed-price contract. This research contributes to the body of knowledge by proposing a theoretical framework that enables both owners and contractors to understand the economics of collaboration in the context of complex projects.

Reverse mortgage (RM) borrowers may get benefit from terminating the contract by selling their house early. For analyzing the termination rate, the authors investigate the rules that govern an elder's decision to sell a house early. The decision is found to be influenced by the strength of the elder's desire to stay in the home, the uncertainty of the elder's death time, and the stochastic price of the house. To more thoroughly elucidate changes in the probability of a sale over time, the authors provide an example illustrating how one can use this decision rule to calculate the probability distribution for selling a house early. Sensitivity analyses are provided to show the influence of the model's parameters on this distribution. Evidence that the model estimates the termination rate more accurately than the traditional model is also provided. The authors' investigation should not only help RM lenders better understand the RM borrower's decision-making process but also help them accurately estimate the RM's termination rate. [ABSTRACT FROM AUTHOR]

The explosive development of the human society in contrast to the limited character of resources determines the need for successful implementation of mathematic models in the decision-making process concerning the use of available resources. One of the critical areas where the need for rigorous criteria for resource allocation is strongly felt is the medical field. This issue appears to be currently affecting the great majority of nations in the world, being considered one of the most important challenges for modern states. The limited amount of resources allocated to the medical system brings forward the importance of optimizing the decision-making process concerning this field using models able to reflect the increasing complexity of the medical system, its interactions with the human society and its dynamics, therefore providing the perturbation control and adjustment instruments. From this point of view, the economical and mathematical modeling of the social phenomena provides strong, elegant and rigorous tools for the description of medical system that appears to be organized as a cybernetic system with a high level of complexity, focused on maximizing the social utility, and allowing the use of cybernetic methods designed for diagnosing, developing automatic medical archives, reducing time consumption and increasing overall efficiency. [ABSTRACT FROM AUTHOR]

Slow steaming is an operational measure in ocean-going vessels sailing at slow speeds. It can help climate mitigation efforts by cutting down marine fuel consumption and consequently reducing CO2 and other Greenhouse Gas Emissions (GHG). Due to climate change both the European Union (EU) and the International Maritime Organization (IMO) are analysing the inclusion of international shipping in the EU Emissions Trading System (ETS) in the near future or alternatively implementing a carbon tax. The paper proposes a methodology to decide the optimal speed of a vessel taking into account its characteristics and the factors that determine its economic results. The calculated cash flow can be used in valuation models. The methodology is applied for a case study for any container ship in a range from 2000 to 20,000 Twenty-foot Equivalent Units (TEU) on a leg of a round trip from Shanghai to Rotterdam. We calculate how speed reduction, CO2 emissions and ship owner’s earnings per year may vary between a business-as-usual scenario and a scenario in which shipping is included in the ETS. The analysis reveals that the optimal speed varies with the size of the vessel and depends on several variables such as marine fuel prices, cargo freight rates and other voyage costs. Results show that the highest optimal speed is in the range of 5500–13,000 TEUs whether or not the ETS is applied. As the number of TEUs transported in a vessel increases emissions per TEU decrease. In an established freight rate market, the optimal speed fluctuates by 1.8 knots. Finally, the medium- and long-term expectations for slow steaming are analysed based on future market prices.

The paper proposes organizing a professional team of the Serbian Army members who would, in addition to their regular duties, assess the hazards, risk and threats of possible explosions of explosive materials and suggest accordingly optimal decisions to decision makers. Operational meetings are defined, followed by the explanation of the importance of training a team of experts for making optimal decisions, in order to reduce the security threat to people and property from the effects of the explosion of explosive materials. The research results and the discussion point to the lack of involvement of other members of the Serbian Army in the basic command functions when proposing solutions for making optimal decisions. It has been emphasized that the findings of the research process would increase the security and safety of all members of the Serbian Army from the effects of explosions of explosive materials. / Служащие Вооруженных Сил Республики Сербия, принимая оптимальные решения непосредственно влияют на возможность предотвращения различных форм опасных происшествий, таких как взрыв взрывчатых средств, который может повлечь за собой катастрофические последствия. Если иметь в виду, что основной характеристикой взрывчатых веществ является быстрое самораспространяющееся химическое превращение (взрыв) с выделением большого количества тепла и газообразных продуктов, под воздействием которых может быть уничтожен весь живой мир, своевременное и правильно принятое решение представляет основание для благовременного устранения всех возможных источников угрозы безопасности для людей и их имущества от взрыва взрывчатых средств. Так как подобные происшествия наступают неожиданно и непредвиденно, или же наступают постепенно, но незаметно, в дальнейшем принимая угрожающую форму. В связи с вышеперечисленными видами опасности, рисков и угроз служащие Вооруженных Сил Республики Сербия при принятии оптимальных решений по снижению последствий взрывов взрывчатых средств должны прилaгать все усилия для предотвращения любой формы неконтролируемого явления, котороеможет привести к взрыву. / Pripadnici Vojske Srbije, donošenjem optimalnih rešenja, preventivno deluju na svaki oblik pojavljivanja neželjenih događaja prilikom eksplozija eksplozivnih sredstava sa katastrofalnim ishodom. Ako se zna da je osnovna karakteristika svih eksplozivnih sredstava oslobađanje velike količine energije hemijskim razlaganjem, koja je sposobna da izvrši mehanički rad na okolinu, uništavajući sav živi svet, onda pravovremena rešenja predstavljaju osnovu za blagovremeno otklanjanje svih mogućih izvora ugrožavanja ljudi i imovine od eksplozije eksplozivnih sredstava. U ovakvim okolnostima negativni događaji nastupaju odjednom i iznenada ili počinju lagano i daljim tokom poprimaju sve izraženije oblike. Imajući u vidu navedene oblike opasnosti, rizika i pretnji, pripadnici Vojske Srbije prilikom donošenja optimalnih rešenja za smanjenje efekata eksplozije eksplozivnih sredstava, moraju nastojati da spreče svaki oblik nekontrolisanog pojavljivanja ovog efekta.