机器人避障问题

研究机器人在平面区域中绕过静态障碍物到达指定目的地的问题, 分别考虑了路程最短和时间最短两种目标下的最优路径, 给出了计算机自动搜索最优路径的模型和算法。     

地面搜索优化方案的模型建立

对一块长为11200 m,宽为7200m的平地矩形区域,运用最优化数学理论,寻求最佳搜索路径.若20人一组搜索,运用整数规划方法建立模型并求解出最短搜索时间为49.03 h;若要在48 h内完成搜索,运用线性规划方法改进模型并求得最少需22人.     

基于遗传算法对规避目标搜索模型

分析了在应召条件下对规避目标搜索行动的特点,然后采用遗传算法建立了可用于辅助搜索决策制定协同搜索方案的模型,为分析应召搜索提供了新的方法,该方法克服了传统的运筹学搜索论在协同行动等复杂条件下寻求最优搜索方案的不足。     

顾客搜索强度影响下短生命周期产品订货决策

根据短生命周期产品的特点,考虑与需求相关的顾客搜索强度,在假设溢出需求为顾客搜索强度函数的情况下,建立了考虑顾客搜索强度因素的斜坡型需求模型,分两种情形对模型最优解进行了存在性证明和求解.然后通过数值算例分析了主要参数变化对缺货时间、订货量、库存成本的影响,发现订货量与顾客搜索强度同方向变动,缺货时间与需求变化临界点出现先后的不同,缺货成本、持有成本和变质成本对库存总成本的影响不同.     

船载直升机目标搜索最佳方案决策模型

根据现代搜索理论的发展,对船载直升机在目标搜索中的具体运用进行了研究,建立了船载直升机目标搜索时搜索力的最优配置模型,解决了在已知目标分布的条件下船载直升机搜索中选择初始探测点、确定搜索路径、确定搜索次数以及搜索效率评估等问题．     

多重因素约束下的网格搜索对策问题研究

首次基于搜索成本及搜索资源等限制因素,构造局中人面向多重约束条件的可行策略集合,建立相应的搜索空间;在给定搜索点权值的基础上,考虑搜索成本与搜索成功概率等因素,构造相应的支付函数,建立多重因素约束下的网格搜索对策模型.为简化模型求解,将对策论问题转化为约束最优化问题,求解约束问题获得最优值,转化为模型的对策值,并给出双方最优混合策略.最后,给出军事想定实例,说明上述模型的实用性及方法的有效性.     

在线时间序列搜索的风险补偿模型

对于在线时间序列搜索问题,在假设对未来信息有一定的预期下,提出了在线时间序列搜索的风险补偿模型,进一步研究了模型的求解,给出了模型的一个最优策略,并通过数值计算讨论了最优策略的补偿函数随参数变化规律.数值实验结果表明,随着风险容忍度的增大与预期区间下限的增大,补偿函数均增大且趋于收敛;随着预期概率的增大与预期区间上限的减少,补偿函数分别增大.研究结果丰富了在线时间序列搜索的理论且具有实际应用价值.     

基于遗传算法的对规避目标搜索模型

分析了在应召条件下对规避目标搜索行动的特点,然后采用遗传算法建立了可用于辅助搜索决策者制定协同搜索方案的模型,为分析应召搜索提供了新的方法,该方法克服了传统的运筹学搜索论在协同行动等复杂条件下寻求最优搜索方案的不足     

无人机灾情巡查区域搜索的建模与求解

采用无人机对地震灾区进行巡查是了解灾情的重要手段,在复杂灾区环境下制定无人机的巡查路线尤为关键.首先针对重点震区灾情巡查问题,构建了带有山体遮挡的区域搜索模型,提出一种基于栅格扫描线的区域搜索算法,从而得到在综合考虑巡查时间、覆盖率、无人机数量以及飞行路线等因素时的最佳巡查方案.其次针对全区域巡查问题,建立了基于区域划分的栅格搜索模型,并提出基于蚁群的改进栅格搜索算法,得到无人机数量少、巡查时间短和巡查路线优的全区域优化巡查方案.     

搜索路径的优化设计模型

研究对指定区域进行全面搜索用时最少的行进路线.问题一中提出了往复式的搜索方式,结合拐弯处所用的时间,得到最优时间为49.806小时,添加三名队员后,最优时间为46.593小时:对问题二提出了分组进行搜索的方式,当分组队员数分别为22、23、5人时,最优时间为20.45小时.     

Optimal searching for a Helix target motion

This paper discusses a search problem for a Helix target motion in which any information of the target position is not available to the searchers. There exist three searchers start searching for the target from the origin. The purpose of this paper is to formulate a search model and finds the conditions under which the expected value of the first meeting time between one of the searchers and the target is finite. Also, the existence of the optimal search plan that minimizes the expected value of the first meeting time is shown. Furthermore,this optimal search plan is found. The effectiveness of this method is illustrated by using an example with numerical results.     

Solving project scheduling problem with the philosophy of fuzzy random programming

Project scheduling problem is to determine the schedule of allocating resources to achieve the trade-off between the project cost and the completion time. In real projects, the trade-off between the project cost and the completion time, and the uncertainty of the environment are both considerable aspects for managers. Due to the complex external environment, this paper considers project scheduling problem with coexisted uncertainty of randomness and fuzziness, in which the philosophy of fuzzy random programming is introduced. Based on different ranking criteria of fuzzy random variables, three types of fuzzy random models are built. Besides, a searching approach by integrating fuzzy random simulations and genetic algorithm is designed for searching the optimal schedules. The goal of the paper is to provide a new method for solving project scheduling problem in hybrid uncertain environments.     

一种改进的公交网络最优路径算法

通过对公交网络模型进行分析,考虑公交线路票价变化,按照出行时间最短同时保证换乘次数较少的原则,对现有解决公交网络最短路问题的算法进行改进.应用了将公交线路抽象为顶点,建立邻接矩阵的方法处理换乘问题.通过实际问题计算验证了算法的有效性.     

On lexicographic optimal solutions in transportation problems

Lexicographic versions of the cost minimizing transportation problem (CMTP) and the time minimizing transportation problem (TMTP) are presented in this paper. In addition to minimizing the quantity sent on the costliest routes in a cost minimizing transportation problem. an attempt is made to minimize the quantity transported on the second-costliest routes. if the shipment on the costliest routes is as small as possible and the quantity shipped on the third-costliest routes, if the shipments on the costliest and the second- costliest routes are as small as possible. and so on. In a lexicographic time minimizing transportation problem one is not only interested in minimizing the transportation cost on the routes of the longest duration but also on the routes of second longest, third-longest duration and so on. For finding lexicographic optimal solutions (LOS) of lexicographic cost minimizing and time minimizing transportation problems a standard cost minimizing transportation problem is formulated whose optimal solution is shown to provide the answer. Some extensions are also discussed     

Definition of the feasible solution set in multicriteria optimization problems with continuous, discrete, and mixed design variables

Engineering optimization problems are multicriteria with continuous, discrete, and mixed design variables. Correct definition of the feasible solution set is of fundamental importance in these problems. It is quite difficult for the expert to define this set. For this reason, the results of searching for optimal solutions frequently have no practical meaning. Furthermore, correct definition of this set makes it possible to significantly reduce the time of searching for optimal solutions. This paper describes construction of the feasible solution set with continuous, discrete, and mixed design variables on the basis of Parameter Space Investigation (PSI) method.     

Learning and forgetting effects on a group scheduling problem

This paper proposes to investigate learning and forgetting effects on the problem of scheduling families of jobs on a single machine to minimize total completion time of jobs. A setup time is incurred whenever the single machine transfers job processing from a family to another family. To analyze the impact of learning and forgetting on this group scheduling problem, we structure three basic models and make some comparisons through computational experiments. The three models, including no forgetting, total forgetting and partial forgetting, assume that the processing time of a job is dependent on its position in a schedule. Some scheduling rules and a lower bound are derived in order to constitute our branch-and-bound algorithm for searching an optimal sequence. In addition, an efficient and simply-structured heuristic is also built to find a near-optimal schedule.     

A combined terminal location and ship routing problem

In this paper, we consider a combined terminal location and ship routing problem at Södra Cell AB. The purpose is to supply the customers' annual demand for pulp products while minimizing the distribution costs. Customers are supplied with various pulp products from pulp mills in Scandinavia by ships, trains, or lorries. The ship routes go from the pulp mills to terminals in Europe. From each terminal, the products are transported to customers by lorry, train, or barge. Some customers can be supplied directly from the pulp mills by trains or lorries. We have developed a mathematical model to select which terminals to use and, at the same time, determine the shipping routes. The mixed integer programming model was solved directly using a commercial solver. When the number of routes generated is large, the time required to obtain an optimal solution is too long. Hence, we have developed heuristics in order to obtain an acceptable solution in reasonable time. In addition to the basic case, five different scenarios were tested. Our heuristics provide solutions that are within 0.12% of the optimal ones.     

New fuzzy models for time-cost trade-off problem

The time-cost trade-off problem is a specific type of the project scheduling problem which studies how to modify project activities so as to achieve the trade-off between the completion time and the project cost. In real projects, the trade-off between the project cost and the completion time, and the uncertainty of the environment are both considerable aspects for managers. In this paper, three new fuzzy time-cost trade-off models are proposed, in which credibility theory is applied to describe the uncertainty of activity duration times. A searching method by integrating fuzzy simulation and genetic algorithm is produced to search the quasi-optimal schedules under some decision-making criteria. The purpose of the paper is to reveal how to obtain the optimal balance of the completion time and the project cost in fuzzy environments.     

Definition of the feasible solution set in multicriteria optimization problems with continuous,discrete, and mixed design variables

Engineering optimization problems are multicriteria with continuous, discrete, and mixed design variables. Correct definition of the feasible solution set is of fundamental importance in these problems. It is quite difficult for the expert to define this set. For this reason, the results of searching for optimal solutions frequently have no practical meaning. Furthermore, correct definition of this set makes it possible to significantly reduce the time of searching for optimal solutions. This paper describes construction of the feasible solution set with continuous, discrete, and mixed design variables on the basis of Parameter Space Investigation (PSI) method.