A Study on Optimizing the Double-Spine Type Flow Path Design for the Overhead Transportation System Using Tabu Search Algorithm

Optimizing Flow Path Design(FPD)is a popular research area in transportation system design,but its application to Overhead Transportation Systems(OTSs)has been limited.This study focuses on optimizing a double-spine flow path design for OTSs with 10 stations by minimizing the total travel distance for both loaded and empty flows.We employ transportation methods,specifically the North-West Corner and Stepping-Stone methods,to determine empty vehicle travel flows.Additionally,the Tabu Search(TS)algorithm is applied to branch the 10 stations into two main layout branches.The results obtained from our proposed method demonstrate a reduction in the objective function value compared to the initial feasible solution.Furthermore,we explore howchanges in the parameters of the TS algorithm affect the optimal result.We validate the feasibility of our approach by comparing it with relevant literature and conducting additional tests on layouts with 20 and 30 stations.

Two-phase tabu search algorithm for solving Chinese high school timetabling problems under the new college entrance examination reform

Upon the latest reform to the college entrance examination in China(i.e.,Gaokao),high schools began implementing an optional class system.Under this scheme,students’time slots become complex,thereby increasing the difficulty in formulating a suitable timetable from the available ones.To address this problem,the coursescheduling model was improved.On the basis of the original hard constraints,the“concurrent group”was considered,and the softer constraints were regarded as optimization goals,such as“teaching plans synchronously”,“no idle periods in the timetables of teachers”,and“evenly distributed lessons”.Given these soft constraints,the model becomes more practical.In this study,a two-phase tabu search algorithm was proposed to solve the problem.The proposed algorithm uses the characteristics of the graph coloring model to eliminate redundant calculations in the neighborhood search process,thereby effectively improving computational efficiency.Fifteen practical instances of different scales were selected for testing to verify the effectiveness of the algorithm.The proposed algorithm can formulate high-quality available timetables(The average satisfaction rate of soft constraints is more than 71%)in a short period.

Tabu Search中集中性和多样性的自适应搜索策略

近年来的研究表明 ,集中性与多样性策略在禁忌搜索中是非常重要的 但集中性与多样性常常又是矛盾的 ,如何解决集中性与多样性之间的矛盾就成为一个值得关注的话题 以组合优化中的著名难题TSP(travelingsalesmanprob lem)为例 ,提出了一种新颖的自适应搜索策略 ,通过邻域和候选集的相互配合 ,动态地调整候选集中分别用于集中性搜索与多样性搜索的元素个数 ,较好地解决了集中性与多样性的冲突问题 仿真实验表明 。

Tabu Search集中性和多样性自动平衡下的增强搜索策略

在禁忌搜索算法中,集中性搜索与多样性搜索是缺一不可但又相互矛盾的两个方面。本文提出了一种在禁忌搜索集中性和多样性自动平衡下的增强搜索策略算法,这种算法在集中性搜索与多样性搜索之间保持合理平衡的同时,又进一步对结果加强集中性搜索或者多样性搜索,以获全局最优解。以组合优化中的典型难题 TSP为例,通过自动更换邻域、候选集,较好地解决了集中性搜索与多样性搜索的冲突。仿真实验表明,解的质量提高了,验证该算法有效。

Tabu search for no-wait flowshop scheduling problem to minimize maximum lateness

In order to solve the no-wait flowshop scheduling problem to minimize the maximum lateness,three job-block-based neighborhoods are proposed,among which the block exchange neighborhood have a size of O（n4）while the block swap and the simplified block exchange neighborhoods have a size of O（n3）.With larger sizes than the existing neighborhoods,the proposed neighborhoods can enhance the solution quality of local search algorithms.Speedup properties for the neighborhoods are developed,which can evaluate a neighbor in constant time and explore the neighborhoods in time proportional to their proposed sizes. Unlike the dominance-rule-based speedup method,the proposed speedups are applicable to any machine number.Three neighborhoods and the union of block swap and the simplified block exchange neighborhoods are compared in the tabu search.Computational results on benchmark instances show that three tabu search algorithms with O（n3）neighborhoods outperform the existing algorithms and the tabu search algorithm with the union has the best performance among all the tested algorithms.

A hybrid algorithm based on tabu search and large neighbourhood search for car sequencing problem

The car sequencing problem(CSP)concerns a production sequence of different types of cars in the mixed-model assembly line.A hybrid algorithm is proposed to find an assembly sequence of CSP with minimum violations.Firstly,the hybrid algorithm is based on the tabu search and large neighborhood search(TLNS),servicing as the framework.Moreover,two components are incorporated into the hybrid algorithm.One is the parallel constructive heuristic(PCH)that is used to construct a set of initial solutions and find some high quality solutions,and the other is the small neighborhood search(SNS)which is designed to improve the new constructed solutions.The computational results show that the proposed hybrid algorithm(PCH+TLNS+SNS)obtains100best known values out of109public instances,among these89instances get their best known values with100%success rate.By comparing with the well-known related algorithms,computational results demonstrate the effectiveness,efficiency and robustness of the proposed algorithm.

一种改进的Tabu Search算法及其在区域电网无功优化中的应用

提出将改进的Tabu(禁忌)搜索算法用于区域电网无功电压优化控制问题的求解.首先根据已知的实际电网的历史数据获得可行的初始解,然后对区域电网采用改进的禁忌搜索方法进行无功优化.在求解的过程中,由于对Tabu表中所记录的"移动"采取"有条件地释放Tabu表中的记录"这一策略,可以使搜索有效地跳出局部极小值点,更好地找到最优解.通过IEEE-14节点算例验证了该算法的有效性.

Channel Assignment Method Using Parallel Tabu Search Based on Graph Theory in Wireless Sensor Networks

Wireless sensor networks are suffering from serious frequency interference.In this paper,we propose a channel assignment algorithm based on graph theory in wireless sensor networks.We first model the conflict infection graph for channel assignment with the goal of global optimization minimizing the total interferences in wireless sensor networks.The channel assignment problem is equivalent to the generalized graph-coloring problem which is a NP-complete problem.We further present a meta-heuristic Wireless Sensor Network Parallel Tabu Search(WSN-PTS) algorithm,which can optimize global networks with small numbers of iterations.The results from a simulation experiment reveal that the novel algorithm can effectively solve the channel assignment problem.

Enhancing the synchronizability of networks by rewiring based on tabu search and a local greedy algorithm

By considering the eigenratio of the Laplacian matrix as the synchronizability measure, this paper presents an efficient method to enhance the synchronizability of undirected and unweighted networks via rewiring. The rewiring method combines the use of tabu search and a local greedy algorithm so that an effective search of solutions can be achieved. As demonstrated in the simulation results, the performance of the proposed approach outperforms the existing methods for a large variety of initial networks, both in terms of speed and quality of solutions.

Energy transmission modes based on Tabu search and particle swarm hybrid optimization algorithm

In China, economic centers are far from energy storage bases, so it is significant to select a proper energy transferring mode to improve the efficiency of energy usage. To solve this problem, an optimal allocation model based on energy transfer mode was proposed after objective function for optimizing energy using efficiency was established, and then, a new Tabu search and particle swarm hybrid optimizing algorithm was proposed to find solutions. While actual data of energy demand and distribution in China were selected for analysis, the economic critical value in comparison between the long-distance coal transfer and electric power transmission was gained. Based on the above discussion, some proposals were put forward for optimal allocation of energy transfer modes in China. By comparing other three traditional methods that are based on regional price differences, freight rates and annual cost with the proposed method, the result indicates that the economic efficiency of the energy transfer can be enhanced by 3.14%, 5.78% and 6.01%, respectively.

A Tabu Search Algorithm for Quadratic 0-1 Programming Problem

In this paper,quadratic 0-1 programming problem (I) is considered, in terms of its features quadratic 0-1 programming problem is solved by linear approxity heurstic algrothm and a developed tabu search ahgrothm .

A two-phase tabu search approach to scheduling optimization in container terminals

An optimization model for scheduling of quay cranes (QCs) and yard trailers was proposed to improve the overall efficiency of container terminals. To implement this model, a two-phase tabu search algorithm was designed. In the QCs scheduling phase of the algorithm, a search was performed to determine a good QC unloading operation order. For each QC unloading operation order generated during the QC's scheduling phase, another search was run to obtain a good yard trailer routing for the given QC's unloading order. Using this information, the time required for the operation was estimated, then the time of return to availability of the units was fed back to the QC scheduler. Numerical tests show that the two-phase Tabu Search algorithm searches the solution space efficiently, decreases the empty distance yard trailers must travel, decreases the number of trailers needed, and thereby reduces time and costs and improves the integration and reliability of container terminal operation systems.

Research on Vehicle Routing Problem with Soft Time Windows Based on Hybrid Tabu Search and Scatter Search Algorithm

With the expansion of the application scope of social computing problems,many path problems in real life have evolved from pure path optimization problems to social computing problems that take into account various social attributes,cultures,and the emotional needs of customers.The actual soft time window vehicle routing problem,speeding up the response of customer needs,improving distribution efficiency,and reducing operating costs is the focus of current social computing problems.Therefore,designing fast and effective algorithms to solve this problem has certain theoretical and practical significance.In this paper,considering the time delay problem of customer demand,the compensation problem is given,and the mathematical model of vehicle path problem with soft time window is given.This paper proposes a hybrid tabu search(TS)&scatter search(SS)algorithm for vehicle routing problem with soft time windows(VRPSTW),which mainly embeds the TS dynamic tabu mechanism into the SS algorithm framework.TS uses the scattering of SS to avoid the dependence on the quality of the initial solution,and SS uses the climbing ability of TS improves the ability of optimizing,so that the quality of search for the optimal solution can be significantly improved.The hybrid algorithm is still based on the basic framework of SS.In particular,TS is mainly used for solution improvement and combination to generate new solutions.In the solution process,both the quality and the dispersion of the solution are considered.A simulation experiments verify the influence of the number of vehicles and maximum value of tabu length on solution,parameters’control over the degree of convergence,and the influence of the number of diverse solutions on algorithm performance.Based on the determined parameters,simulation experiment is carried out in this paper to further prove the algorithm feasibility and effectiveness.The results of this paper provide further ideas for solving vehicle routing problems with time windows and improving the efficiency of vehicle routing problems and have strong applicability.

Dynamic Tabu Search Algorithm for Solving Departure Scheduling Problem

The aircraft departure scheduling problem is described comprehensively. A mathematical model is built for solving this problem. Then, a local search algorithm is proposed; based on it, the dynamic tabu search technique is applied, and the related implement techniques are presented. A simulation including condition and results is performed to solve a representative problem. It is concluded that （ 1 ） departure aircrafts of each queue keep the same order comparatively all the lime, and the distribution of the departure time is well-proportioned, which accords with the ＂first-come first-serve＂ principle; （2） the total time costs are minimized, which would economize money and reduce danger; （ 3 ） the optimization result is not exclusive, which means that several approaches can be chosen at will; （4） the solution obtained is the global optimal one, which guarantees the validity of the proposed method.

基于改进Tabu Search算法的配电线路无功运行优化系统控制策略研究

在配电网无功补偿优化过程中,Tabu Search算法能够高效地将最优解搜索出来,因此,将Tabu Search算法应用于配电网无功补偿优化具有现实可操作性。本文对Tabu Search方法的原理进行了详细介绍,因为农村配电网线路具备很多特点,综合考量其并联电容器投切等问题及特点,本文在Tabu Search的基础上,进行了一系列改进,用来解决配电网的投切优化问题。提出了基于电容器投切分组的二进制编码优化,基于无功补偿的损耗降低特点,根据功率传输方向,对权重根据由低到高的顺序排列,然后进行二进制编码,从二进制编码串的末端进行移动;Tabu Search非常依赖于初始解,提出了当前时段处于运行退出状态时,根据无功缺额电容器的配置方式进行。

Integrating Tabu Search in Particle Swarm Optimization for the Frequency Assignment Problem

In this paper, we address one of the issues in the frequency assignment problem for cellular mobile networks in which we intend to minimize the interference levels when assigning frequencies from a limited frequency spectrum. In order to satisfy the increasing demand in such cellular mobile networks, we use a hybrid approach consisting of a Particle Swarm Optimization(PSO) combined with a Tabu Search(TS) algorithm. This approach takes both advantages of PSO efficiency in global optimization and TS in avoiding the premature convergence that would lead PSO to stagnate in a local minimum. Moreover, we propose a new efficient, simple, and inexpensive model for storing and evaluating solution's assignment. The purpose of this model reduces the solution's storage volume as well as the computations required to evaluate thesesolutions in comparison with the classical model. Our simulation results on the most known benchmarking instances prove the effectiveness of our proposed algorithm in comparison with previous related works in terms of convergence rate, the number of iterations, the solution storage volume and the running time required to converge to the optimal solution.

Dominance property based tabu search for single machine scheduling problems with family setups

The problem of minimizing the maximum lateness on a single machine with family setups is considered.To solve the problem, dominance property is studied and then introduced into the tabu search（TS） algorithm.With the dominance property, most unpromising neighbors can be excluded from the neighborhood, which makes the search process always focus on the most promising areas of the solution space.The proposed algorithms are tested both on the randomly generated problems and on the real-life problems.Computational results show that the proposed TS algorithm outperforms the best existing algorithm and can solve the real-life problems in about 1.3 on average.

Heuristic tabu search scheduling algorithm for wet-etching systems in semiconductor wafer fabrications

To improve overall equipment efficiency(OEE) of a semiconductor wafer wet-etching system,a heuristic tabu search scheduling algorithm is proposed for the wet-etching process in the paper,with material handling robot capacity and wafer processing time constraints of the process modules considered.Firstly,scheduling problem domains of the wet-etching system(WES) are assumed and defined,and a non-linear programming model is built to maximize the throughput with no defective wafers.On the basis of the model,a scheduling algorithm based on tabu search is presented in this paper.An improved Nawaz,Enscore,and Ham(NEH) heuristic algorithm is used as the initial feasible solution of the proposed heuristic algorithm.Finally,performances of the proposed algorithm are analyzed and evaluated by simulation experiments.The results indicate that the proposed algorithm is valid and practical to generate satisfied scheduling solutions.

Berth-crane allocation under uncertainty:dynamic modeling and nested Tabu search

The integrated berth-crane allocation problem at container terminals is addressed under the uncertainty of vessel arrival time at operational level. To ensure both robustness and flexibility of the 2-stage decision processes,a dynamic decision framework is proposed based on the dynamic analysis of information and operation at container terminal. A mixed integer programming model is established aiming at minimizing total cost of all vessels,including the cost of fixed to-be-executed decisions in the 1^(st) stage and expected cost of the adjustable stochastic-scenario-based decisions of all scenarios in the 2^(nd) stage. A multi-layer nested Tabu search is proposed for each epoch dynamically. Finally numerical experiments have been conducted to testify the effectiveness and efficiency of the proposed model and algorithm.

Capacitated Dynamic Facility Location Problem Based on Tabu Search Algorithm

Facility location problem is a kind of NP-Hard combinational problem.Considering ever-changing demand sites,demand quantity and releasing cost,we formulate a model combining tabu search and FCM(fuzzy clustering method) to solve the capacitated dynamic facility location problem.Some results are achieved and they show that the proposed method is effective.