Multiperiod Location-Routing with Decoupled Time Scales

This paper focuses on a multiperiod discrete facility location problem where transportation costs are considered together with location costs to design the operating facility pattern along a time horizon. The problem captures the difference in the scope of the location and routing decisions by considering different scales within the time horizon. Thus, solutions to this problem reflect the stability of locational decisions along time. The high complexity of this problem makes it impossible to be solved in practice with commercial software. For this reason, an approximation based on replacing vehicle routes by spanning trees is proposed, and its capability for providing good quality solutions is assessed in a series of computational experiments.     

Calculating risk neutral probabilities and optimal portfolio policies in a dynamic investment model with downside risk control

This paper presents a method for solving multiperiod investment models with downside risk control characterized by the portfolio’s worst outcome. The stochastic programming problem is decomposed into two subproblems: a nonlinear optimization model identifying the optimal terminal wealth distribution and a stochastic linear programming model replicating the identified optimal portfolio wealth. The replicating portfolio coincides with the optimal solution to the investor’s problem if the market is frictionless. The multiperiod stochastic linear programming model tests for the absence of arbitrage opportunities and its dual feasible solutions generate all risk neutral probability measures. When there are constraints such as liquidity or position requirements, the method yields approximate portfolio policies by minimizing the initial cost of the replication portfolio. A numerical example illustrates the difference between the replicating result and the optimal unconstrained portfolio.     

Urban rapid transit network capacity expansion

This paper examines a multi-period capacity expansion problem for rapid transit network design. The capacity expansion is realized through the location of train alignments and stations in an urban traffic context by selecting the time periods. The model maximizes the public transportation demand using a limited budget and designing lines for each period. The location problem incorporates the user decisions about mode and route. The network capacity expansion is a long-term planning problem because the network is built over several periods, in which the data (demand, resource price, etc.) are changing like the real problem changes. This complex problem cannot be solved by branch and bound, and for this reason, a heuristic approach has been defined in order to solve it. Both methods have been experimented in test networks.     

多阶段M-SV投资组合优化的离散近似迭代法研究

文章提出了离散近似迭代法,用该方法求解具有交易成本和交易量限制的多阶段均值一半方差(M-sV)投资组合模型.离散近似迭代方法的基本思路为:首先,将连续型状态变量离散化,根据网络图的构造方法将上述模型转化多阶段赋权有向图;其次,运用嘉量原理求出起点至终点的最长路程,即获得模型的一个可行解;最后,以该可行解为基础,继续迭代直到前后两个可行解非常接近.文章还证明了该方法的收敛性和复杂性.     

多周期Probit模型中MLE的存在性

本文我们讨论了多周期Probit模型中MLE的存在性问题,给出了当协方差阵已知时,参数的MLE存在的充要条件;当协方差阵未知但具有序列结构时,参数的MLE存在的一个必要条件和一个充分条件.     

A memetic algorithm for the multiperiod vehicle routing problem with profit

In this paper, we extend upon current research in the vehicle routing problem whereby labour regulations affect planning horizons, and therefore, profitability. We call this extension the multiperiod vehicle routing problem with profit (mVRPP). The goal is to determine routes for a set of vehicles that maximizes profitability from visited locations, based on the conditions that vehicles can only travel during stipulated working hours within each period in a given planning horizon and that the vehicles are only required to return to the depot at the end of the last period. We propose an effective memetic algorithm with a giant-tour representation to solve the mVRPP. To efficiently evaluate a chromosome, we develop a greedy procedure to partition a given giant-tour into individual routes, and prove that the resultant partition is optimal. We evaluate the effectiveness of our memetic algorithm with extensive experiments based on a set of modified benchmark instances. The results indicate that our approach generates high-quality solutions that are reasonably close to the best known solutions or proven optima, and significantly better than the solutions obtained using heuristics employed by professional schedulers.     

Multiperiod Mean-Variance Optimization with Intertemporal Restrictions

We investigate mean-variance optimization problems that arise in portfolio selection. Restrictions on intermediate expected values or variances of the portfolio are considered. Some explicit procedures for obtaining the solution are presented. The main advantage of this technique is that it is possible to control the intermediate behavior of a portfolio’s return or variance. Some examples illustrating these situations are presented. The first author received financial support from CNPq (Brazilian National Research Council) Grants 472920/03-0 and 304866/03-2, FAPESP (Research Council of the State of S?o Paulo) Grant 03/06736-7, PRONEX Grant 015/98, and IM-AGIMB.     

Portfolio selection with transaction costs under expected shortfall constraints

An investor subject to proportional transaction costs allocates funds to multiple stocks and a bank account, to maximise the expected growth rate of the portfolio value under Expected Shortfall (ES) constraints. In a numerical example with ten time steps and one stock important innovations are caused by the introduction of the Expected Shortfall constraint: First, expected returns are reduced by less than one-tenth when the ES constraint is introduced. In comparison, economic capital as measured by ES, is reduced to amounts between one-half and three-quarters, when the ES constraint is introduced. Second, the dependence of expected return and ES on the initial portfolio, in particular when transaction costs are high, is largely removed by the introduction of the ES constraint.     

A note on the Swiss Solvency Test risk measure

In this paper we examine whether the Swiss Solvency Test risk measure is a coherent measure of risk as introduced in Artzner et al. [Artzner, P., Delbaen, F., Eber, J.M., Heath, D., 1999. Coherent measures of risk. Math. Finance 9, 203–228; Artzner, P., Delbaen, F., Eber, J.M., Heath, D., Ku, H., 2004. Coherent multiperiod risk adjusted values and Bellman’s principle. Working Paper. ETH Zurich]. We provide a simple example which shows that it does not satisfy the axiom of monotonicity. We then find, as a monotonic alternative, the greatest coherent risk measure which is majorized by the Swiss Solvency Test risk measure.