New solution concepts for n-decision maker conflicts based on generalized metarationalities for modelling possible human behaviour under conflict are proposed. A classification of these solution concepts, also called stability definitions, is presented both to simplify understanding and to illustrate important differences among different stability regimes. The relationships among solution concepts are explored and new, more specific results are obtained in the comparison among existing stability concepts and the newly proposed ones. An informative example is used to demonstrate the applicability and insights of these solution concepts.

In this paper, we investigate a kind of truck-door assignment problem in a crossdock. Multiple related realistic constraints such as the capacity of trucks, the capacity of temporary storage area, the time windows of trucks as well as the operational time inside the crossdock are considered and therefore, make the assignment problem strongly NP-hard and very challenging. A two-stage genetic algorithm is proposed to solve this problem and the experimental results show the superiority of this approach in comparison to CPLEX solver in terms of effectiveness and efficiency, especially for the large-scale instances. That is, the decision making process can speed up and a near optimal truck-door assignment scheme can be obtained within a relatively short time by applying this two-stage approach in practice.

Nowadays, more and more transactions or interactions like online dating and shopping are completed on two-sided platforms involving two groups of agents. On these two-sided platforms, there often exist cross-network effects, i.e., the benefits that agents at one side receive are positively related to the number of agents at the other side, and vice versa. This paper considers such two-sided platforms, where the platforms offer a certain service to attract agents of both sides to join the platforms, and then charge agents who join the platforms a lump-sum fee to gain the profit. We present service and pricing strategies for both monopolistic and duopolistic platforms, respectively. We also investigate the impact of platforms’ life cycle on their service and pricing strategies. Some managerial implications are shown.

This paper is about predicting the outcome of tennis matches of the Association of Tennis Professionals (ATP) and the Women’s Tennis Association (WTA) using both data and judgments. There are many factors that influence that outcome. An important question is which factors have significant influence on the outcome. We have identified numerous factors and systematically prioritized them subjectively and objectively, so as to improve the accuracy of the prediction. We then used them to predict the win-lose outcome of the 2015 US OPEN tennis matches (63 men and 31 women’s games) before they took place. The tennis match prediction in sports literature thus far reported an accuracy rate of 70%.The accuracy of our proposed model which combines data and judgment reaches 85.1%

As the status of order picking in the warehousing and distribution system has been raised, the work-rest scheduling of picking becomes particularly important. Although science and technology have developed rapidly, manual picking is still essential and indispensable. However, previous researches focused on the study of the sequencing, ignoring human factors. The paper presents a work-rest schedule model in parts to picker picking system. Two objectives are proposed that include minimizing the picking time and minimizing picking error rate. And workers’ fatigue, workload is taken into account in the manual order picking systems because the fatigue can have a large influence on the picking time and the picking error rate. A genetic algorithm is used to solve a multi-objective optimization problem that the model concerns and looking for a Pareto front as the most effective methods for solving this problem. Once the original data is given, the work-rest scheduling model is built and the work sequence, and the number of breaks are determined to be chosen by decision makers. In addition, a case study of the model is used to confirm that the model is effective and it is necessary to consider the human factor in the picking system.

This paper constructs a dynamic conflict model that considers Decision Makers’ (DMs) evolutional attitude using the option prioritization. The proposed evolutional attitude approach is based on the framework of the Graph Model for Conflict Resolution (GMCR). Compared with the existing state-based preference, the option prioritization is a more convenient and efficient approach to analyze larger models with consideration of the evolutional attitude, which exists broadly in the evolutional conflicts in real-life. This study reveals how the evolutional attitude of a DM succeeds in the overall evolution of conflict. The analysis unfolds that DMs change their attitude(s) consequent upon the changes in DMs and options available to them as conflict evolves from one level to the next. The changes in attitude of DMs during dynamic conflict situation have substantial effects on the equilibrium outcomes of a conflict. The proposed evaluation attitude-based approach is employed to analyze the conflict between the Punjab Government (G) and Heritage Campaigner and the Public (P) in Pakistan that appeared due to the inappropriate design, planning, and construction of an urban transport system project in Lahore, Pakistan. The present study demonstrates the modeling procedure of a two-level evolutional attitude-based conflict analysis. The results of the stability analysis reveal that improper (negative) attitude may result in undesirable and unexpected consequences, such as project temporalities and delays. This research provides a foundation for future research in urban project planning that employs strategic ways to avoid disputes caused by DMs’ attitudes.

The goal of this paper is to develop a direct method for computing interval Banzhaf values for a class of interval cooperative games. In this method, it is proven that the Banzhaf values of the associated cooperative games of interval cooperative games are monotonic and non-decreasing functions of coalitions’ payoffs under weaker coalition monotonicity-like conditions. So the interval Banzhaf values can be explicitly obtained through using only the lower and upper bounds of the coalitions’ interval payoffs, respectively. The proposed method does not employ interval subtractions and hereby can effectively avoid the irrational issues such as irreversibility and uncertainty enlargement. We prove some important and desirable properties of the interval Banzhaf values and illustrate the applicability and validity of the proposed method with a numerical example.