Target setting: An application to a bank branch network

In this paper we examine the performance of the target setting procedure employed by a large financial institution in Spain to evaluate the operating performance of its branch offices. We begin by evaluating the ability of the branch offices to meet the targets established by bank management. We then evaluate the targets themselves, and we find that the list of targets can be substantially reduced without significant loss or distortion of information to bank management. We then re-evaluate the performance of branch offices on the basis of a reduced set of influential targets.     

Integrated bank performance assessment and management planning using hybrid minimax reference point – DEA approach

The purpose of assessing past performances and setting future targets for an organisation such as a bank branch is to find where the branch stands in comparison to its peers within the bank branch network and how to improve the efficiency of its operations relatively when compared to the best practice branches. However, future performance targets may be set arbitrarily by the head-office and thus could be unrealistic and not achievable by a branch. A hybrid minimax reference point-data envelopment analysis (HMRP-DEA) approach is investigated to incorporate the value judgements of both branch managers and head-office directors and to search for the most preferred solution (MPS) along the efficient frontier for each bank branch. The HMRP-DEA approach is composed of three minimax models, including the super-ideal point model, the ideal point model and the shortest distance model, which share the same decision and objective spaces, are different from each other only in their reference points and weighting schema, and are proven to be equivalent to the output-oriented DEA dual models. These models are examined both analytically and graphically in this paper using a case study, which provides the unprecedented insight into integrated efficiency and trade-off analyses. The HMRP-DEA approach uses DEA as an ex-post-facto evaluation tool for past performance assessment and the minimax reference point approach as an ex-ante planning tool for future performance forecasting and target setting. Thus, the HMRP-DEA approach provides an alternative means for realistic target setting and better resource allocation. It is examined by a detailed investigation into the performance analysis for the fourteen branches of an international bank in the Greater Manchester area.     

Cost efficiency,production and value-added models in the analysis of bank branch performance

This paper develops a framework for performance appraisal in the context of a bank branch network. A data envelopment analysis model is advocated that can identify both input and output inefficiencies from a cost minimization perspective. The model is then applied to the analysis of a bank branch network and the production and value-added approaches are deployed jointly to give a comprehensive assessment of bank branch efficiency. The sources of underperformance are identified and their managerial implications are explored.     

Evaluating the financial performance of bank branches

We evaluate the financial performance of most of the branch offices of a large European savings bank for a recent accounting period. We employ a complementary pair of nonparametric techniques to evaluate their financial performance, in terms of their ability to conserve on the expenses they incur in building their customer bases and providing customer services. We find variation in the ability of branch offices to perform this task, and agreement on the identity of the laggard branches. We then employ parametric techniques to determine that the list of indicators on which their financial performance is evaluated can be reduced without statistically significant loss of information to bank management. Both findings suggest ways in which the bank can increase the profitability of its branch network. A previous version of this paper was presented at CORE, Université Catholique de Louvain, Louvain-la-Neuve, Belgium, where we received many helpful comments from the audience. We are grateful to three referees for their helpful comments as well.     

Investigation of selection strategies in branch and bound algorithm with simplicial partitions and combination of Lipschitz bounds

Speed and memory requirements of branch and bound algorithms depend on the selection strategy of which candidate node to process next. The goal of this paper is to experimentally investigate this influence to the performance of sequential and parallel branch and bound algorithms. The experiments have been performed solving a number of multidimensional test problems for global optimization. Branch and bound algorithm using simplicial partitions and combination of Lipschitz bounds has been investigated. Similar results may be expected for other branch and bound algorithms.     

A combinatorial optimization algorithm for solving the branchwidth problem

In this paper, we consider the problem of computing an optimal branch decomposition of a graph. Branch decompositions and branchwidth were introduced by Robertson and Seymour in their series of papers that proved the Graph Minors Theorem. Branch decompositions have proven to be useful in solving many NP-hard problems, such as the traveling salesman, independent set, and ring routing problems, by means of combinatorial algorithms that operate on branch decompositions. We develop an implicit enumeration algorithm for the optimal branch decomposition problem and examine its performance on a set of classical graph instances.     

Commercial branch performance evaluation and results communication in a Canadian bank––a DEA application

In this paper, we focus on evaluating the performance of the commercial branches of a large Canadian bank using data envelopment analysis. Two production models are considered in this country-wide evaluation. One model, looking directly at resource usage, is most useful to the branch manager. The other model, incorporating financial results, is more geared towards senior management. We introduce non-discretionary factors to reflect specific aspects of the environment a branch is operating in, such as risk and economic growth rate of the region. Both input and output multipliers are constrained by incorporating market prices as well as managerial preferences, in order to get effectiveness measures. The cost-minimisation study led to valuable results pertaining to the performance of individual branches. Notable is the methodology introduced here that shows how to present graphical and numeric outcomes to managers. Gap maps, pie charts and target tables are produced for each branch to provide performance goals for the managers. Useful information has also been obtained at the district level. Output oriented models were analysed to reflect the Bank's recent emphasis towards growth in some areas.     

Digital filtering of stochastic-network decision-node noise

Digital filtering techniques are utilized to counteract serial correlation in random-number sequences generated during discrete-event stochastic-network simulations. An algorithm is described which monitors departures from Bernoulli decision-node branch probabilities and compensates for observed serial correlation. Relationships between branch probability and system performance are then explored.     

数学建模与聚类分析方法在企业经营效绩评价中的综合运用

本论文通过CT总公司所属九个分公司财务指标即:财务效益状况指标,资产营运状况指标,偿债能力状况指标,发展能力状况指标和稳固程度状况指标五个方面的财务状况数据,一方面采用数理统计方法进行数据分析,建立数学模型,设定了评分办法及评分标准.做出了CT总公司所属九个分公司2 0 0 0年的经营业绩(量化)评价结果.另一方面按九个公司财务指标的原始数据用聚类分析的方法将其归类,进一步揭示出各个公司之间的联系与差别.     

Lower Bound Improvement and Forcing Rule for Quadratic Binary Programming

In this paper several equivalent formulations for the quadratic binary programming problem are presented. Based on these formulations we describe four different kinds of strategies for estimating lower bounds of the objective function, which can be integrated into a branch and bound algorithm for solving the quadratic binary programming problem. We also give a theoretical explanation for forcing rules used to branch the variables efficiently, and explore several properties related to obtained subproblems. From the viewpoint of the number of subproblems solved, new strategies for estimating lower bounds are better than those used before. A variant of a depth-first branch and bound algorithm is described and its numerical performance is presented.     

Linking customer satisfaction, employee appraisal, and business performance: an evaluation methodology in the banking sector

The linkage among customer satisfaction, employee evaluation, and business performance data is very important in modern business organizations. Several previous research efforts have studied this linkage, focusing mainly on the financial or business performance in order to analyze the efficiency of an organization. However, recent studies have tried to consider other important performance indicators, which are able to affect business operations and future growth (e.g., external and internal customer satisfaction). In the case of the banking industry, studying the relations among the aforementioned variables is able to give insight in the performance evaluation of bank branches and the viability analysis of the banking organization. This paper presents a real-world study for measuring the relative efficiency of a set of bank branches using a Data Envelopment Analysis (DEA) approach. In particular, a multistage DEA network model is proposed, using a set of performance indicators that combine customer satisfaction, employee evaluation, and business performance indices. The main aim of the presented study is to evaluate the relative efficiency of each customer service delivery step, in the environment of a bank branch. The results are also able to estimate the contribution of the assessed performance indicators to the branch’s overall efficiency, and to determine potential improvement actions.     

Minimizing total tardiness on a two-machine re-entrant flowshop

We present a branch and bound algorithm for a two-machine re-entrant flowshop scheduling problem with the objective of minimizing total tardiness. In the re-entrant flowshop considered here, all jobs must be processed twice on each machine, that is, each job should be processed on machine 1, machine 2 and then machine 1 and machine 2. By regarding a job as a pair of sub-jobs, each of which represents a pass through the two machines, we develop dominance properties, a lower bound and heuristic algorithms for the problem, and use these to develop a branch and bound algorithm. For evaluation of the performance of the algorithms, computational experiments are performed on randomly generated test problems and results are reported. Results of the experiments show that the suggested branch and bound algorithm can solve problems with up to 20 sub-jobs in a reasonable amount of CPU time, and the average percentage gap of the heuristic solutions is about 13%.     

A branch and reduce approach for solving a class of low rank d.c. programs

Various classes of d.c. programs have been studied in the recent literature due to their importance in applicative problems. In this paper we consider a branch and reduce approach for solving a class of d.c. problems. Seven partitioning rules are analyzed and some techniques aimed at improving the overall performance of the algorithm are proposed. The results of a computational experience are provided in order to point out the performance effectiveness of the proposed techniques.     

Minimizing makespan on a two-machine re-entrant flowshop

This paper focuses on a two-machine re-entrant flowshop scheduling problem with the objective of minimizing makespan. In the re-entrant flowshop considered here, all jobs must be processed twice on each machine, that is, each job should be processed on machine 1, machine 2 and then machine 1 and machine 2. We develop dominance properties, lower bounds and heuristic algorithms for the problem, and use these to develop a branch and bound algorithm. For evaluation of the performance of the algorithms, computational experiments are performed on randomly generated test problems. Results of the experiments show that the suggested branch and bound algorithm can solve problems with up to 200 jobs in a reasonable amount of CPU time.     

Solving a class of low rank d.c. programs via a branch and bound approach: A computational experience

Various classes of d.c. programs have been studied in the recent literature due to their importance in applicative problems. In this paper we consider a branch and bound approach for solving a class of d.c. problems. Both stack policies and partitioning rules are analyzed, pointing out their performance effectiveness by means of the results of a computational experience.     

具有机器适用限制的分布式置换流水车间问题的模型与算法

考虑具有机器适用限制的多个不同置换流水车间的调度问题. 机器适用限制指的是每个工件只能分配到其可加工工厂集合. 所有置换流水车间拥有的机器数相同但是具有不同的加工能力. 首先, 针对该问题建立了基于位置的混合整数线性规划模型; 进而, 对一般情况和三种特殊情况给出了具有较小近似比的多项式时间算法. 其次, 基于NEH方法提出了启发式算法NEHg, 并给出了以NEHg为上界的分支定界算法. 最后, 通过例子说明了NEHg启发式算法和分支定界算法的计算过程, 并进行大量的实验将NEHg与NEH算法结果进行比较, 从而验证了NEHg算法的有效性.     

A Parallel Interior Point Method and Its Application to Facility Location Problems

We present a parallel interior point algorithm to solve block structured linear programs. This algorithm can solve block diagonal linear programs with both side constraints (common rows) and side variables (common columns). The performance of the algorithm is investigated on uncapacitated, capacitated and stochastic facility location problems. The facility location problems are formulated as mixed integer linear programs. Each subproblem of the branch and bound phase of the MIP is solved using the parallel interior point method. We compare the total time taken by the parallel interior point method with the simplex method to solve the complete problems, as well as the various costs of reoptimisation of the non-root nodes of the branch and bound. Computational results on two parallel computers (Fujitsu AP1000 and IBM SP2) are also presented in this paper.     

Optimization of a Long-Short Portfolio under Nonconvex Transaction Cost

The purpose of this paper is to propose a practical branch and bound algorithm for solving a class of long-short portfolio optimization problem with concave and d.c. transaction cost and complementarity conditions on the variables.We will show that this algorithm can solve a problem of practical size and that the long-short strategy leads to a portfolio with significantly better risk-return structure compared with standard purchase only portfolio both in terms of ex-ante and ex-post performance.     

Using DEA and survival analysis for measuring performance of branches in New Zealand's Accident Compensation Corporation

This paper describes an approach to solving the problem of assessing relative branch performance in the Accident Compensation Corporation (ACC), the New Zealand state-owned, no-fault, personal injury compensation insurance company. The methodology described in this paper is innovative in that it assesses relative performance via a modified data envelopment analysis (DEA) process. Performance is assessed and can be examined in terms that are meaningful to business goals. Performance evaluation has generally aligned well with management preconceptions of performance. DEA results are clustered to find common performance themes that are reviewed for business acceptability and the successful themes are used to measure performance against a Farrell frontier. The methodology is applicable to other situations where there are multiple instances of a unit performing the same or similar functions. Technical analysis as used in this paper is based on survival analysis, DEA, clustering and knowledge of the organisation's business operations and objectives.     

Yard crane scheduling in port container terminals

Yard cranes are the most popular container handling equipment for loading containers onto or unloading containers from trucks in container yards of land scarce port container terminals. However, such equipment is bulky, and very often generates bottlenecks in the container flow in a terminal because of their slow operations. Hence, it is essential to develop good yard crane work schedules to ensure a high terminal throughput. This paper studies the problem of scheduling a yard crane to perform a given set of loading/unloading jobs with different ready times. The objective is to minimize the sum of job waiting times. A branch and bound algorithm is proposed to solve the scheduling problem optimally. Efficient and effective algorithms are proposed to find lower bounds and upper bounds. The performance of the proposed branch and bound algorithm is evaluated by a set of test problems generated based on real life data. The results show that the algorithm can find the optimal sequence for most problems of realistic sizes.