The generalized lock scheduling problem: An exact approach

The present paper introduces an integrated approach to solving the generalized lock scheduling problem. Three interrelated sub problems can be discerned: ship placement, chamber assignment and lockage operation scheduling. In their turn, these are closely related to the 2D bin packing problem, the assignment problem and the (parallel) machine scheduling problem respectively. In previous research, the three sub problems mentioned were considered separately, often using (heuristic) interaction between them to obtain better solutions. A mixed integer linear programming model is presented and applied to instances from both inland locks and locks in a tide independent port. The experiments show that small instances incorporating a wide range of real-life constraints can be solved to optimality.     

Locating a Biorefinery in Northern Spain: Decision Making and Economic Consequences

Biofuels are emerging as a prominent renewable and sustainable energy sources in developed countries. In this sense, this paper presents a case study in which a biorefinery has to be sited in Northern Spain. Thus, the strategic decision of locating such a facility is deeply investigated through strategic policy evaluation. Then, tactical decisions ranging from purchasing and transportation policies to storage protocols are carried out. Only local and limited biomass can be harvested for supplying the biorefinery through a heterogeneous vehicle fleet. Moreover two different and mutually exclusive storage strategies are evaluated: direct supply from crops to biorefinery and using intermediate-collectors. Additionally, crop exploitation factors and biorefinery sizes are used to generate several scenarios in which the strategic decision of location as well as all the tactic decisions are made. Some mixed integer linear programming models are proposed to figure out all relevant decision problems.The results suggest that the Northwest study area as the best option to locate the biorefinery and recommend the intermediate-collector storage strategy. Moreover, the key information about critical biomass, crops and times are also provided.     

Airline new route selection using compromise programming - The case of Taiwan-Europe

The decision to launch a new route has a huge effect on the outcomes of airlines in the market. In order to find potential destinations for airlines, this paper utilizes a compromise programming method for selecting direct flight routes. The selection framework comprises two objective functions, with one maximizing total revenue and the other minimizing total cost. A case studying Taiwan-European region destinations is interpreted in the analysis. The results indicate that four potential routes, including Madrid, Milan, Munich and Zurich should be added to the airlines’ service destinations. Therefore, this research suggested that the airport authority could apply incentives scheme to attract carriers to open new routes and add flight frequencies to strengthen its competitiveness.     

Pareto efficient allocation of an in-motion wireless charging infrastructure for electric vehicles in a multipath network

Electric vehicles (EV) use an eco-friendly technology that limits the greenhouse gas emissions of the transport sector, but the limited battery capacity and the density of the battery are the major barriers to the widespread adoption of EV. To mitigate this, a good method seems to be the innovative wireless charging technology called ‘On-Line EV (OLEV)’, which is a contactless electric power transfer technology. This EV technology has the potential to charge the vehicle’s battery dynamically while the vehicle is in motion. This system helps to reduce not only the size of the battery but also its cost, and it also contributes to extending the driving range before the EV has to stop. The high cost of this technology requires an optimal location of the infrastructure along the route. For this reason, the objective of this paper is to study the problem of the location of the wireless charging infrastructure in a transport network composed of multiple routes between the origin and the destination. To find a strategic solution to this problem, we first and foremost propose a nonlinear integer programming solution to reach a compromise between the cost of the battery, which is related to its capacity, and the cost of installing the power transmitters, while maintaining the quality of the vehicle’s routing. Second, we adapt the multi-objective particle swarm optimization (MPSO) approach to our problem, as the particles were robust in solving nonlinear optimization problems. Since we have a multi-objective problem with two binary variables, we combine the binary and discrete versions of the particle swarm optimization approach with the multi-objective one. The port of Le Havre is presented as a case study to illustrate the proposed methodology. The results are analyzed and discussed in order to point out the efficiency of our resolution method.     

数控仿真软件在数控教学中的应用——以车削零件加工为例

为了提高《数控机床与编程》课程的教学质量,把数控仿真软件应用引入到课堂教学,并结合车削零件加工,展示数控仿真软件整体加工过程,结果极大提高学生课堂的兴趣,提高了教学效果,也提高学生的数控编程能力和数控机床操作能力,保证了教学质量。     

A fuzzy goal programming approach to analyse sustainable development goals of India

Energy policy, environmental planning and economic development play a key role in sustainable development. Sustainable development requires suitable and strategic policies satisfying multiple and conflicting objectives. Fuzzy goal programming (FGP) is a well-known approach in multi-criteria decision-making for its practical application. In this article, a FGP approach is proposed to analyse environmental, energy and sustainability goals of India by the year 2030 with reference to the key economic sectors of India. The presented model analyses the improvement opportunities, requirement of efforts and implementation of the sustainable development plans. Numerical illustration is also provided for validation and application of the proposed model.     

An integrated replenishment-recruitment policy in a sustainable retailing system for deteriorating products

Currently, retail facilities play a significant role both economically and socially for their contributions to job creation and to reducing unemployment. In this paper, economic, environmental, and social issues, including unemployment, job creation for the local workforce within their hometown, the immigration of an unemployed workforce, and the naturalization of non-natives are addressed for a retailer. We explore the class of deteriorating products from the viewpoint of its economic and environmental features. Then, a linear multi-objective mathematical model is developed to determine an integrated replenishment and recruitment policy for the retailer in the direction of sustainability. Using data from the flower industry, a numerical analysis is presented. The results indicate that if necessary facilities and infrastructures are provided to permanently settle qualified immigrants, both social and economic indicators will be improved. We also determine that by concentrating on strategies such as job creation for natives through retail facilities with no increase in production capacity and by applying careful policies for immigration and naturalization, social welfare can be improved.     

Robust Markowitz mean‐variance portfolio selection under ambiguous covariance matrix

This paper studies a robust continuous‐time Markowitz portfolio selection problem where the model uncertainty affects the covariance matrix of multiple risky assets. This problem is formulated into a min–max mean‐variance problem over a set of nondominated probability measures that is solved by a McKean–Vlasov dynamic programming approach, which allows us to characterize the solution in terms of a Bellman–Isaacs equation in the Wasserstein space of probability measures. We provide explicit solutions for the optimal robust portfolio strategies and illustrate our results in the case of uncertain volatilities and ambiguous correlation between two risky assets. We then derive the robust efficient frontier in closed form, and obtain a lower bound for the Sharpe ratio of any robust efficient portfolio strategy. Finally, we compare the performance of Sharpe ratios for a robust investor and for an investor with a misspecified model.     

基于改进Dijkstra算法的最短路算法

Dijkstra算法是求解最短路径问题的经典算法。在现如今的城市交通网络中,经常需要寻求两个地点之间的最短距离,减少运输时间。本文将Dijkstra算法与C语言相结合,对Dijkstra算法进行改进,根据实际网络图的情况,建立了相应的数学模型,运用C语言编程,在给定的网络图中,实现了只需确定起始点和终点,就可以直接输出最短路径和最短距离的功能。在有多个相同最短路径的情况下,会将多个最短路径一起输出,在搜索到终点时,立即跳出,结束循环。在一般情况下,无需对所有点进行迭代,提高了效率。这种方法可以应用到现在的物流运输中,以此来节约时间,降低成本。     

关于节水型园林设计规划的思路构架和分析

随着我国社会主义现代化建设和城市化建设进程不断加快,人们对自然资源的过渡开发与利用,带来了诸多环境问题。为提高我国园林生态水平,相关部门应认识到我国园林用水的现状,并积极开发和设计节水型园林,大力推广节水灌溉,优化各类植物配置,加强园林人力资源管理,提高人们的节水意识,从而为建设节水型园林奠定坚实的基础。