A water distribution problem in the Mexican Valley is modeled first as a three-person noncooperative game. Each player has a five-dimensional strategy vector, the strategy sets are defined by 15 linear constraints, and the three payoff functions are also linear. A nonlinear optimization problem is first formulated to obtain the Nash equilibrium based on the Kuhn-Tucker conditions, and then, duality theorem is used to develop a computational procedure. The problem can also be considered as a conflict between the three players. The non-symmetric Nash bargaining solution is suggested to find the solution. Multiobjective programming is an alternative solution concept, when the water supply of the three players are the objectives, and the water authority is considered to be the decision maker. The optimal water distribution strategies are determined by using these solution concepts and methods.

The aim of this study is Implementation of productivity Management Cycle with Operational Kaizen Approach to Improve Production Performance in Pars Khodro Car Corporation. In this intervention study, all 120 employees of the Pars Khodro Company's Brilliance Body Production Unit were involved. After implementation of 9 steps of Kaizen, Kaizen questionnaire was completed by the staff. The questionnaire of employee performance evaluation was completed by direct supervisor before and after implementation of Kaizen. Finally, the collected data were analyzed using descriptive and analytical statistics using SPSS22. The significance level was considered 0.05. In According to the findings, Kaizen has a significant effect on all functional areas of the staff (Pvalue <0.05). Without much financial investment and new technologies, using the existing facilities and relying on the capabilities and creativity of the organization's staff can be achieved more efficiency.

This paper presents a multistage stochastic programming model to deal with multi-period, cardinality constrained portfolio optimization. The presented model aims to minimize investor's expected regret, while ensuring achievement of a minimum expected return. To generate scenarios of market index returns, a random walk model based on the empirical distribution of market-representative index returns is proposed. Then, a single index model is used to estimate stock returns based on market index returns. Afterward, historical returns of a number of stocks, selected from Frankfurt Stock Exchange (FSE), are used to implement the presented scenario generation method, and solve the stochastic programming model. In addition, the impact of cardinality constraints, transaction costs, minimum expected return and predetermined investor's target wealth are investigated. Results show that the inclusion of cardinality constraints and transaction costs significantly influences the investors risk-return tradeoffs. This is also the case for investors target wealth.