Binary Programming Model Research Articles

Alocação otimizada de dispositivos de controle e proteção em redes de distribuição

A Alocação e/ou realocação otimizada de dispositivos de controle e proteção em redes de distribuição de energia elétrica melhora a qualidade do serviço de fornecimento de energia e os índices de confiabilidade do sistema. Neste trabalho apresenta-se um modelo de programação não linear binário (PNLB) para o problema de alocação e/ou realocação de chaves seccionadoras e dispositivos de proteção em alimentadores radiais aéreos de distribuição. As restrições consideradas no modelo refletem limitações técnicas e econômicas, tais como problemas de coordenação de dispositivos de proteção em série, número de equipamentos disponíveis, importância do alimentador sob análise, topologia do circuito, qualidade do fornecimento de energia e limitações físicas do sistema. Para solução desse problema propõe-se um algoritmo de Busca Tabu Reativo (RTS). São apresentados os resultados obtidos através de testes realizados com a implementação computacional da metodologia proposta, utilizando-se um alimentador de distribuição radial real com 134 barras.

A Second-Order Cone Programming Method for Multiuser Detection Problem

Based on the binary quadratic programming model of the CDMA maximum likelihood multiuser detection problem, a detection strategy by the second-order cone programming method is presented. The proposed method relaxes the binary quadratic programming model as a second-order cone programming model. Coupled with the sign function, a suboptimal solution is obtained for the multiuser detection problem. Comparing with the reported semidefinite programming method, simulations demonstrate that the second-order cone programming method often yields the similar bit error rate (BER) performances for the multiuser detection problem, but the average CPU time of this method is significantly reduced.

A Multi-Stage Approach to Time-Cost Trade-Off Analysis using Mathematical Programming

Time-cost trade-offs are a critical construction planning issue, which have received significant amount of research. Many existing solutions are based on evolutionary algorithms, which are search-based and ignore the structure of time-cost trade-off problems. Mathematical programming methods were applied previously but their computational limitations have been widely recognized. This study proposed a multi-stage approach based on linear programming and integer programming to improve the efficiency of time-cost trade-off analysis using mathematical programming. Three models are used in this approach- a normal duration model, a reduction time model, and an adjustment model. The normal duration model finds the normal project duration. The reduction time model seeks optimum solutions to minimize the total cost subject to a project deadline by assuming all crash-able activities are linear-continuous (LC). The adjustment model finds feasible solution for non-linear-continuous (NLC) activities whose reduction time given by the reduction model is not reasonable. It is a pure binary programming model. Using this approach, the reduction time model narrows down the number of NLC activities that need reduction time adjustment. This step improves the adjustment model computational efficiency. A case study issued to demonstrate the application and the potential of this approach.

Operational workforce planning for check-in counters at airports

Abstract This paper addresses operation models for workforce planning for check-in systems at airports. We characterize different tasks of the hierarchical workforce planning problem with time-dependent demand. A binary linear programming formulation is developed for the fortnightly tour scheduling problem with flexible employee contracts. This binary programming model is solved for optimality by CPLEX for real-world demand scenarios with different workforce sizes. The numerical study analyzes the impact of the degree of flexibility and economies of scale. The model formulation is extended to generate convenient tours with regard to employee preferences.

A spatial decision support system for the optimal environmental reclamation of open-pit coal mines in Greece

Mine reclamation is an integral part of the mineral development process. The selection of land use after the mine closure is a difficult decision, which is complicated further because of the variety of parameters that must be taken into account trying to provide the local community with a viable development plan. Conventional methods used for reclamation planning are characterised by the lack of data integration and by time-consuming analysis. In this study, we propose a spatial decision-support system (SDSS) that minimises these problems, as data integration and analysis are offered within one computerised environment. A geographical information system and multi-criteria decision-making methods, based on binary integer linear programming models, have been integrated to select the appropriate land use in different parts of a post-mining area taking into account social, technical, economic, environmental and safety criteria. The proposed SDSS was used for the selection of the optimal landscape reclamation strategy of the Amynteon lignite surface mine located at West Macedonia Lignite Centre, Northern Greece. On the basis of developed mine maps, the model variables are assessed and incorporated into the objective optimisation function. Emphasis is placed on the spatial diversification of the model variables. The application demonstrates that the decision-support system allows the mining company to determine in an efficient way the specific land use (agricultural land, forest, recreational area and industrial zone) that is considered the most suitable for every part of the study area.

A Novel Nonlinear Programming Model for Distribution Protection Optimization

This paper presents a novel nonlinear binary programming model designed to improve the reliability indices of a distribution network. This model identifies the type and location of protection devices that should be installed in a distribution feeder and is a generalization of the classical optimization models given in the literature. This new approach is more flexible and leads to better placement solutions. Numerical results of the tests performed on real feeders are presented for analysis. Furthermore, we make the reliability data of the 36 feeders that were used in our work available to the research community.

Centralized bid evaluation for awarding of construction projects – A case of India government

Reviewing the procedures of contractor selection in government departments in various countries and in the Rural Development Department (RDD) in India, this paper brings out several weaknesses of the current contractor selection procedure. It suggests a centralized contractor evaluation process with the inclusion of three new selection attributes along bid price. The suggested attributes are: (1) time quoted to complete the project, (2) warranty period quoted, and (3) past performance score of the contractor. To solve the resulting multi-objective decision-making problem, the paper proposes a binary goal programming model. When tested with the existing contractor selection procedure for six past projects in RDD, the model yields the same results as those taken by RDD in the past, confirming the credibility of the model. When tested with the suggested procedure, the model yields much superior results.

Solving a comprehensive model for multiobjective project portfolio selection

Any organization is routinely faced with the need to make decisions regarding the selection and scheduling of project portfolios from a set of candidate projects. We propose a multiobjective binary programming model that facilitates both obtaining efficient portfolios in line with the set of objectives pursued by the organization, as well as their scheduling regarding the optimum time to launch each project within the portfolio without the need for a priori information on the decision-maker's preferences. Resource constraints, the possibility of transferring resources not consumed in a given a period to the following one, and project interdependence have also been taken into account. Given that the complexity of this problem increases as the number of projects and the number of objectives increase, we solve it using a metaheuristic procedure based on Scatter Search that we call SS-PPS (Scatter Search for Project Portfolio Selection). The characteristics and effectiveness of this method are compared with other heuristic approaches (SPEA and a fully random procedure) using computational experiments on randomly generated instances. Statement of scope and purpose This paper describes a model to aid in the selection and scheduling of project portfolios within an organization. The model was designed assuming strong interdependence between projects, which therefore have to be assessed in groups, while allowing individual projects to start at different times depending on resource availability or any other strategic or political requirements, which involves timing issues. The simultaneous combination of project portfolio selection and scheduling under general conditions involves known drawbacks that we attempt to remedy. Finally, the model takes into account multiple objectives without requiring a priori specifications regarding the decision-maker's preferences. The resolution of the problem was approached using a metaheuristic procedure, which showed by computational experiments good performance compared with other heuristics.

Binary fuzzy goal programming approach to single model straight and U-shaped assembly line balancing

Abstract Assembly line balancing generally requires a set of acceptable solutions to the several conflicting objectives. In this study, a binary fuzzy goal programming approach is applied to assembly line balancing. Models for balancing straight and U-shaped assembly lines with fuzzy goals (the number of workstations and cycle time goals) are proposed. The binary fuzzy goal programming models are solved using the methodology introduced by Chang [Chang, C.T., 2007. Binary fuzzy goal programming. European Journal of Operational Research 180 (1), 29–37]. An illustrative example is presented to demonstrate the validity of the proposed models and to compare the performance of straight and U-shaped line configurations.

Centralized construction contractor selection considering past performance of contractors: a case of India

Analyzing the contractor selection procedures of government departments in various countries and in the Rural Development Department (RDD) in India, this paper bring out several weaknesses of the present contractor selection procedure. It suggests the inclusion of three new selection attributes and the adoption of a centralized contractor evaluation process. The suggested attributes are: time quoted to complete the project, warranty period quoted, and past performance score of the contractor. To obtain the past performance score of a contractor, the paper uses a fuzzy multi-attribute utility scoring technique that allows consideration of qualitative/quantitative and enabling/inhibiting character of the relevant attributes. To solve the resulting multi-attribute–multi-objective decision-making problem, the paper proposes a fuzzy binary goal programming model. When tested with the existing contractor selection procedure for three past projects in RDD, the model yields the same results as those taken by RDD in the past, confirming the credibility of the model. When tested with the suggested procedure, the model yields much superior results.

The Minisum Multipurpose Trip Location Problem on Networks

We investigate multipurpose trip location problems on networks with two different types of facilities and three groups of customers, two of which need only one type of service, while the third group needs both types of service in a single trip. The objective is to minimize the total weighted travel distance of all trips. We prove that there exists a dominating location set for the problem on a general network, propose a general binary programming model, and analyze the properties of optimal solutions on networks with simple topologies and one facility per type. We also investigate several heuristic approaches to the problem on general networks and present extensive computational experiments.

Binary fuzzy goal programming

Goal programming is an important technique for solving many decision/management problems. Fuzzy goal programming involves applying the fuzzy set theory to goal programming, thus allowing the model to take into account the vague aspirations of a decision-maker. Using preference-based membership functions, we can define the fuzzy problem through natural language terms or vague phenomena. In fact, decision-making involves the achievement of fuzzy goals, some of them are met and some not because these goals are subject to the function of environment/resource constraints. Thus, binary fuzzy goal programming is employed where the problem cannot be solved by conventional goal programming approaches. This paper proposes a new idea of how to program the binary fuzzy goal programming model. The binary fuzzy goal programming model can then be solved using the integer programming method. Finally, an illustrative example is included to demonstrate the correctness and usefulness of the proposed model.

A New Computer Algorithm for Simultaneous Test Construction of Two-Stage and Multistage Testing

This paper discusses the simultaneous approach for test generation of two-stage and multistage tests from an item bank. However, most previous test generation problems involved binary programming models, and the efficiency of available solution algorithms is the major concern for these problems. Therefore, this study considers two important concepts on the solution process, i.e., alternative ways to formulate mathematical models and alternative solution algorithms. Based on these two concepts, this paper is two-fold. First, two binary programming models with a special network structure that would be explored computationally are presented for modeling these problems. The first model maximizes test information function at one specified ability point and the second model matches the target test information function at several specified ability points as closely as possible. Second, an efficient special-purpose network algorithm is then used to solve these two models. Hence, the test construction process tends to be improved in terms of both computational efforts and quality of tests. An empirical study shows the results in line with the above two criteria.

A goal programming approach to mixed-model assembly line balancing problem

In this paper, a binary goal programming model for the mixed-model assembly line balancing (ALB) problem is developed. The model is based on the concepts developed by Patterson and Albracht [1] and the model of Deckro and Rangachari [2] developed for the single-model ALB problem. The proposed model provides a considerable amount of flexibility to the decision maker since several conflicting goals can be simultaneously considered.

Demurrage costs optimization in ports using binary mathematical programming models

SODA is a system by which the schedule of ships in a port can be found in order to minimize the demurrage and operating costs associated with shipping operations. SODA constructs and resolves binary programming models using shipping data (arrival dates, demurrage costs, berths to be used, etc.) and available berths in a planning horizon. The model is of an adjustable precision: major accuracy implies greater calculation time. SODA provides an optimal result to a complex problem in a resolution time which is generally better than that needed for a manual solution.

Manufacturing cell formation in the presence of lot splitting and multiple units of the same machine

We present a realistic cell formation problem in the design of cellular manufacturing systems which includes three important features. First, when multiple units of a machine type are considered due to processing time requirements, the model accounts for assigning the units to different cells if such an assignment contributes to reducing material handling costs. Second, the model accounts for the possibility of performing two or more nonconsecutive operations of a part on the same machine. Finally, the model allows for splitting the lot into two if the total workload required of a part's operation on a machine exceeded its daily unit capacity expressed in manned hours. We refer to this feature as ‘lot splitting’. Consequently, the operation required of each split lot of the part can be performed on a separate unit (machine). The model formulated for the problem falls into the class of generalized quadratic binary programming models. As the problem is shown NP-hard in the strong sense, a higher level heuri...

A biary integer programming approach for simultaneous machine-part grouping in cellular manufacturing systems

This paper presents the development of a comprehensive model and the identification of a suitable solution technique for evaluating the effectiveness of simultaneous part-machine groupings in cellular manufacturing systems. The objective function of the model is formulated as maximizing a unified measure of effectiveness evaluated as a weighted sum of fractions representative of the (negative of) total moves and in-cell utilizations. All of the operational constraints associated with setting-up a cellular manufacturing system are included in the model. These represent processing time requirements of parts on machines, sequence of operations, non-consecutive operations scheduled to be performed on the same machine, machine capacities, and the limitation set on the maximum number of machines that can be assigned to a cell. The model assumes that the desired number of manufacturing cells can be determined a priori by the management of the parts manufacturing company. The original model, formulated as a quadratic binary programming model, is subsequently converted into a linear binary programming model. The model is implemented by solving an example problem chosen from published literature, and the solution obtained is proven to be superior to that obtained from previous models.

Simultaneous machine-part grouping approach in manufacturing cells

We present a comprehensive model including all of the operational constraints for solving a cell formation problem in cellular manufacturing systems. It is formulated as a generalized quadratic binary programming model with the objective of minimizing total moves evaluated as a weighted sum of inter- and intracell moves. Two most significant operational constraints included in the model are the sequence of operations associated with each part and the capability of assigning machines of the same type to different cells if two or more machines are considered due to workload requirements. The original model is Transformed into a linear binary programming model, and an example problem is solved using a commercial programming package. The final assignment of parts and machines to cells result in a lower total move than that evaluated from a previous study for the same problem.

An automated test development of parallel tests from a seed test

Binary programming models are presented to generate parallel tests from an itembank. The parallel tests are created to match item for item an existing seed test and match user supplied taxonomic specifications. The taxonomic specifications may be either obtained from the seed test or from some other user requirement. An algorithm is presented along with computational results to indicate the overall efficiency of the process. Empirical findings based on an itembank for the Arithmetic Reasoning section of the Armed Services Vocational Aptitude Battery are given.

Data and reports: Contents design and users allocation

When a common information system should supply data in a batch processing mode to many various users, the systems analyst is faced with the problem of allocating data among various reports and reports among different users. The traditional approach to that problem is very unstructured. Such a problem is formulated here in a nonlinear binary programming model. Four alternative techniques of solving the model are presented, followed by an example. The main contribution is a systematic and analytic approach toward a major problem in information systems design.