Business Information and Decision Systems

Evaluating and optimizing e-government services is imperative for governments especially due to the capacity of e-services to transform public administrations and assist the interactions of governments with citizens, businesses and other government agencies. Existing widely applied evaluation approaches neglect to incorporate citizens' satisfaction measures. Several citizen satisfaction models and indicators have been suggested in academia; however a reference process model that can assist practitioners to apply these performance measures is missing. In this paper we draw upon the evaluation approach proposed by the EU funded project CEES and propose a reference process model that captures re-usable practices for e-government evaluation from a citizens' perspective. The novelty of the proposed approach is that using DEA for evaluating the e-services the assessment results in suggestions for strategic improvement of the e-services.

The operating theater layout problem (OTLP) in a hospital aims to determine for a set of facilities their positions and orientations on the floor-layout of departments in a hospital subject to a set of constraints on distances, available areas, and non-overlapping facilities according to international medical standards and specifications. The OTLP has two main objectives: a quantitative objective to minimize the interdepartmental travel costs among facilities and a second qualitative objective to maximize the closeness rating among facilities. In this paper, a mixed integer linear programming (MILP) model is proposed for OTLP. The MILP model is validated on two illustrative cases to determine the positions as well as the orientations of facilities in a two-dimensional space for a two-floor hospital using commercial optimization software.

The vehicle routing problem (VRP) under capacity and distance restrictions involves the design of a set of minimum cost delivery routes, originating and terminating at a central depot, which services a set of customers. Each customer must be supplied exactly once by one vehicle route. The total demand of any vehicle must not exceed the vehicle capacity. The total length of any route must not exceed a pre-speeified bound. Approximate methods based on descent, hybrid simulated annealing/tabu search, and tabu search algorithms are developed and different search strategies are investigated. A special data structure for the tabu search algorithm is implemented which has reduced notably the computational time by more than 50%. An estimate for the tabu list size is statistically derived. Computational results are reported on a sample of seventeen bench-mark test problems from the literature and nine randomly generated problems. The new methods improve significantly both the number of vehicles used and the total distances ~avelled on all results reported in the literature.

This bibliography contains 500 references on four classical routing problems: the Traveling Salesman Problem, the Vehicle Routing Problem, the Chinese Postman Problem, and the Rural Postman Problem. References are presented alphabetically under a number of subheadings. Shmoys [303], Menger [333], Miiller-Merbach [346], Reinelt [406], Voigt [487]. 2.2. APPLICATIONS Bland and Shallcross [55], Eiselt and Laporte [156]. 2.3. FORMULATIONS AND EXACT ALGORITHMS FOR THE ASYMMETRICAL TSP Carpaneto, Fischetti and Toth [83], Desrochers and Laporte [122], Finke, Claus and Gunn [168], Fischetti and Toth [171], Langevin, Soumis and Desrosiers [279], Miller and Pekny [336], Padberg and Sung [371], Pekny and Miller [384], Wong [494]. 2.4. FORMULATIONS AND EXACT ALGORITHMS FOR THE SYMMETRICAL TSP Cornurjols, Fonlupt and Naddef [108], Fischetti, Gonzalez and Toth [169], Fleischmann [181], Grrtschel and Holland [221], Grrtschel and Padberg [222], Land [277], Laporte [280], Martin [329], Naddef and Rinaldi [348], Padberg and Grrtschel [367], Padberg and Rinaldi [368,369,370], Padberg and Sung [371]. 2.5. HEURISTICS FOR THE TSP Bartholdi and Platzman [29, 30], Bentley [45], Bonomi and Lutton [64], Braun [71 ], Carlier and Villon [81 ], Codenotti and Margara [ 104], Fiechter [ 167], Gendreau, Hertz and Laporte [198], Glover [208], Gu and Huang [225], Jeong and Kim [251], Johnson [252], JiJnger, Reinelt and Thienel [254], Kinderwater and Savelsbergh G. Laporte, LH. Osrnan, A bibliogaphy of routing problems [261], Knox [262, 263], Lee and Choi [304], Mak and Morton [323], Malek [325],

Metaheuristics are the most exciting development in approximate optimization techniques of the last two decades. They have had widespread successes in attacking a variety of difficult combinatorial optimization problems that arise in many practical areas. This bibliography provides a classification of a comprehensive list of 1410 references on the theory and application of metaheuristics. Metaheuristics include but are not limited to Constraint logic programming; Greedy random adaptive search procedures; Natural evolutionary computation; Neural networks; Non-monotonic search strategies; Space-Search methods; Simulated annealing; Tabu search; Threshold algorithms and their hybrids. References are presented in alphabetical order under a number of subheadings.

Focused issue on applied meta-heuristics In recent years, there have been significant advances in the theory and applications of meta-heuristics to the determination of approximate solutions for complex optimization problems. A meta-heuristic is an iterative master process that guides and modifies the operations of subordinate heuristics to efficiently produce high quality solutions. It may combine intelligently different concepts to explore the search space using adaptive learning strategies and structured information. The family of meta-heuristics can be classified into three categories and their hybrids. Construction-based meta-heuristics include greedy random adaptive search method, guided construction methods, and ant colony systems. Local-searchbased meta-heuristics include simulated annealing, noisy methods, guided local search methods, iterated local search, neural networks, tabu search, threshold accepting, and variable neighborhood search. Population-based meta-heuristics include evolutionary methods, genetic algorithms, path re-linking, and scatter search. For a good introduction on meta-heuristics, we refer to and .

Achieving effective coordination among suppliers and retailers has become a pertinent research issue in supply chain management. Channel coordination is a joint decision policy achieved by a supplier(s) and a retailer(s) characterized by an agreement on the order quantity and the trade credit scenario (e.g., quantity discounts, delay in payments). This paper proposes a centralized model where players in a two-level (supplier-retailer) supply chain coordinate their orders to minimize their local costs and that of the chain. In the proposed supply chain model the permissible delay in payments is considered as a decision variable and it is adopted as a trade credit scenario to coordinate the order quantity between the twolevels. Computational results indicate that with coordination, the retailer orders in larger quantities than its economic order quantity, with savings to either both players, or to one in the supply chain. Moreover, a profit-sharing scenario for the distribution of generated net savings among the players in the supply chain is presented. Analytical and experimental results are presented and discussed to demonstrate the effectiveness of the proposed model.

The weighted maximal planar graph (WMPG) problem seeks to find a subgraph from a given weighted complete graph such that the subgraph is planar-it can be embedded on the plane without any arcs intersecting. The subgraph is maximal-no additional arc can be added to the subgraph without destroying its planarity and it also has the maximal sum of arc weights. In this paper, the main objective is to develop, implement and empirically analyse a new greedy random adaptive search procedure (GRASP) to solve the WMPG problem. A dynamic strategy to update the restricted candidate list is proposed. An efficient data structure is developed for the Green&Al-Hakim (GH) construction heuristic. The data structure reduces the GH complexity from Oðn 3 Þ to Oðn 2 Þ:

An efficient and effective tabu search implementation for the weighted maximal planar graph problem is proposed. The search incorporates a number of novel features including: the introduction of a new set of two-move operators; a move-cache-memory structure for efficiently searching the neighbourhood space; and a random roulette selection from a ranked list of best moves for diversification. The effects of these and other features on solution quality are investigated. Computational results are reported on a set of 100 benchmark instances of sizes varying from 20 to 100 vertices. The results demonstrate that the new probabilistic tabu search algorithm is very competitive with state of the art algorithms in the literature in terms of both solution quality and computational effort.

In the capacitated clustering problem (CCP), a given set of n weighted points is to be partitioned into p clusters such that, the total weight of the points in each cluster does not exceed a given cluster capacity. The objective is to find a set of p centers that minimises the total scatter of points allocated to these centers. In this paper, we propose a merger of Greedy Random Adaptive Search Procedure (GRASP) and Adaptive Memory Programming (AMP) into a new GRAMPS framework for the CCP. A learning process is kept in charge of tracking information on the best components in an elite set of GRAMPS solutions. The information are strategically combined with problem-domain data to restart the construction search phase. At early stage of constructions, priorities are given to problem-domain data and progressively shifted towards generated information as the learning increases. GRAMPS is implemented with an efficient local search descent based on a restricted k-interchange neighbourhood. Extensive experiments are reported on on a standard set of bench-marks from the literature and on a new set of large instances. The results show that GRAMPS has an efficient learning mechanism and is competitive with the existing methods in the literature.

E-government services involve many stakeholders who have different objectives that can have an impact on success. Among these stakeholders, citizens are the primary stakeholders of government activities. Accordingly, their satisfaction plays an important role in e-government success. Although several models have been proposed to assess the success of e-government services through measuring users' satisfaction levels, they fail to provide a comprehensive evaluation model. This study provides an insight and critical analysis of the extant literature to identify the most critical factors and their manifested variables for user satisfaction in the provision of e-government services. The various manifested variables are then grouped into a new quantitative analysis framework consisting of four main constructs: cost; benefit; risk and opportunity (COBRA) by analogy to the well-known SWOT qualitative analysis framework. The COBRA measurement scale is developed, tested, refined and validated on a sample group of e-government service users in Turkey. A structured equation model is used to establish relationships among the identified constructs, associated variables and users' satisfaction. The results confirm that COBRA framework is a useful approach for evaluating the success of e-government services from citizens' perspective and it can be generalised to other perspectives and measurement contexts.

This paper proposes a three-level (supplier-manufacturer-retailer) supply chain model with a profit sharing mechanism to maximise the supply chain profit. In this model, an all-unit price discounts scheme is used to coordinate the order quantities among the supply chain levels, and the demand at the retailer's end is assumed to be price dependent. To enhance the coordination in the supply chain, two profit-sharing scenarios are investigated. The semi-liberal scenario is based on increasing the quantity discount in order to generate more demands with which the most powerful player in the chain will get the highest fraction of additional profits. However, a strict mechanism is suggested to rectify the first scenario by dividing the coordination profits based on equal return on investments. Computational results are provided under different patterns of the players' order or set-up costs along the chain. Furthermore, the results show that the strict mechanism is the best mechanism for profit sharing among the players in the supply chain.

The appraisal and relative performance evaluation of nurses are very important and beneficial for both nurses and employers in an era of clinical governance, increased accountability and high standards of health care services. They enhance and consolidate the knowledge and practical skills of nurses by identification of training and career development plans as well as improvement in health care quality services, increase in job satisfaction and use of cost-effective resources. In this paper, a data envelopment analysis (DEA) model is proposed for the appraisal and relative performance evaluation of nurses. The model is validated on thirty-two nurses working at an Intensive Care Unit (ICU) at one of the most recognized hospitals in Lebanon. The DEA was able to classify nurses into efficient and inefficient ones. The set of efficient nurses was used to establish an internal best practice benchmark to project career development plans for improving the performance of other inefficient nurses. The DEA result confirmed the ranking of some nurses and highlighted injustice in other cases that were produced by the currently practiced appraisal system. Further, the DEA model is shown to be an effective talent management and motivational tool as it can provide clear managerial plans related to promoting, training and development activities from the perspective of nurses, hence increasing their satisfaction, motivation and acceptance of appraisal results. Due to such features, the model is currently being considered for implementation at ICU. Finally, the ratio of the number DEA units to the number of input/output measures is revisited with new suggested values on its upper and lower limits depending on the type of DEA models and the desired number of efficient units from a managerial perspective.

In the Vehicle Routing Problem with Backhauls (VRPB), a central depot, a fleet of homogeneous vehicles, and a set of customers are given. The set of customers is divided into two subsets. The first (second) set of linehauls (backhauls) consists of customers with known quantity of goods to be delivered from (collected to) the depot. The VRPB objective is to design a set of minimum cost routes; originating and terminating at the central depot to service the set of customers. In this paper, we develop a self-organizing feature maps algorithm, which uses unsupervised competitive neural network concepts. The definition of the architecture of the neural network and its learning rule are the main contribution. The architecture consists of two types of chains: linehaul and backhaul chains. Linehaul chains interact exclusively with linehaul customers. Similarly, backhaul chains interact exclusively with backhaul customers. Additonal types of interactions are introduced in order to form feasible VRPB solution when the algorithm converges. The generated routes are then improved using the well-known 2-opt procedure. The implemented algorithm is compared with other approaches in the literature. The computational results are reported for standard benchmark test problems. They show that the proposed approach is competitive with the most efficient metaheuristics.