Forming minimum-cost machine cells with exceptional parts using zero-one integer programming

Minimum-energy broadcast and multicast in wireless networks: An integer programming approach and improved heuristic algorithms

Optimal sequencing of tasks in an aluminium smelter casthouse

High blood pressure or hypertension is a global public health issue. High blood pressure can lead to cardiovascular disease, stroke, diabetes and others. The diet problem of high blood pressure patients has always been concerned by the field of operational research. Some previous and recent research have proposed that diet plays an important role in affecting the condition of high blood pressure. A balanced diet will provide essential nutrients for high blood pressure patients that help to control and lower blood pressure. The purpose of this study is to construct a diet menu that meet the nutritional requirements of high blood pressure patient as well as minimize the food cost by developing a mathematical model using linear and integer programming approaches. The model of this study involved 10 type of food groups with 413 types of food variables based on the Malaysian recipes. The findings show that integer programming is a good alternative for linear programming. Integer programming leads to an optimal and effective solutions for the diet problem of high blood pressure patients.

Cell formation deals with grouping of machines and parts in manufacturing systems according to their compatibility. Manufacturing processes are surrounded with an abundance of complex constraints which should be considered carefully and represented clearly for obtaining high efficiency and productivity. Constraint programming is a new approach to combinatorial optimization and provides a rich language to represent complex constraints easily. However, the cell formation problems are well suited to be solved by constraint programming approach since the problem has many constraints such as part-machine requirements, availabilities in the system in terms of capacity, machine and worker abilities. In this study, the cell formation problem is modeled using machine, part processing and worker flexibilities via resource element–based representation. Resource elements define the processing requirements of parts and processing capabilities of machines and workers, which are resource-independent capability units. A total of 12 case problems are generated, and different search phases of constraint programming are defined for the solution procedure. The cell formation problem is modeled in both constraint programming and integer programming, and a comparative analysis of constraint programming and integer programming model solutions is done. The results indicate that both the models are effective and efficient in the solution of the cell formation problem.

In this paper, we propose several integer programming approaches with a polynomial number of constraints to formulate and solve the minimum connected dominating set problem. Further, we consider both the power dominating set problem – a special dominating set problem for sensor placement in power systems – and its connected version. We propose formulations and algorithms to solve these integer programs, and report results for several power system graphs.

The current study presents a zero-one integer programming approach to determine the minimum break point set for the coordination of directional relays. First, the network is reduced if there are any parallel lines or three-end nodes. Second, all the directed loops are enumerated to reduce the iteration. Finally, the problem is formulated as a set-covering problem, and the break point set is determined using the zero-one integer programming technique. Arbitrary starting relay locations and the arbitrary consideration of relay sequence to set and coordinate relays result in navigating the loops many times and futile attempts to achieve system-wide relay coordination. These algorithms are compared with the existing methods, and the results are presented. The problem is formulated as a setcovering problem solved by the zero-one integer programming approach using LINGO 12, an optimization modeling software.

Research and development (R&D) is often a well spring of new ideas and concepts leading to the development of commercially viable products and processes. An organization’s future market and financial positions may depend in large measure on the R&D project proposals which are selected. A variety of financial, market, technical, and manufacturing criteria may influence the selection decision. The importance of specific criteria varies by type of R&D activity, and the extent to which a particular project supports business objectives. This paper describes an approach for modeling the R&D project selection decision using the Analytic Hierarchy Process. The AHP represents an improvement over other well-known scoring approaches since the criteria weights or priorities established by the AΗΡ are not based on arbitrary scales, but use a ratio scale for human judgments. The paper begins with a brief review of the R&D project selection literature, leading to a description of the desired characteristics for a decision support system for project selection. For a specific R&D strategy, namely, new product development, an AHP model is developed using an illustrative example. For situations requiring a large number of projects to be evaluated, the AΗΡ model is expanded to include a series of performance ratings for each criterion. The performance ratings and weights for each criterion are transferred to a spreadsheet program which produces the final project rankings. The resulting project priorities or scores are included in an integer programming model to assist in the project funding decisions. The relationship between the integer programming approach and a form of benefit-cost analysis is discussed and illustrated. Two extensions of the AHP approach are then presented. The first addresses situations requiring the evaluation of a broader set of project selection criteria. The second illustrates how the AHP project selection model can be linked to the strategic planning process through an analysis of the mission, objectives, and strategies of the business. The paper concludes with a discussion of future areas of research.

Material transfer is one of the most important activities in the production process activities and has a close relationship with the design of the layout of production facilities. A manufacturing company engaged in the manufacture and assembly of machine spare parts at the oil palm plant constraints in terms of material handling so that the decline in utility of the production floor layout and the increasing cost of moving raw materials. To improve the utility on the production floor using group technology method that is Rank Order Clustering (ROC) and Similarity Coefficient (SC). From the result of matrix rank calculation in pairs or between machines then SC method is the best layout design with decreasing material displacement moment by 56,86%. And to improve the layout of facilities on the production floor using BLOCPLAN algorithm that is the value of the degree of Adjency Score of 0.5317. This proposed layout provides a smaller displacement moment so as to shorten the processing time of all parts by 338 minutes and increase utility on the production floor.

This paper presents an integer programming model and algorithm for an electric utility capacity expansion problem which considers the option of investing in nondispatchable or renewable energy sources. A branch-and-bound algorithm is proposed for this problem in which the continuous relaxation of the subproblem associated with each node in the enumeration tree is solved via an efficient two-phase procedure. This procedure solves a deterministic approximation of the problem in the first phase in order to determine a quick near-optimal solution. The resulting solution is subsequently refined in a second phase using more accurate techniques to represent the negative load due to the renewable sources, and to perform the probabilistic production costing. This technique conserves about 80% of the effort which would be required without the deterministic phase. An implementation of this approach is described for the Tijuana-Mexicali subsystem of the Mexican utility, which is not connected to the rest of the Mexican electric system, and which faces a very high summer peak load and a comparatively low winter load. The results suggest that along with a prescribed capacity expansion of conventional equipments, the utility should invest in some solar cooling systems, and, more pertinently, should involve itself intensely in conservation measures in homes of individual customers.

Obtaining the Grundy chromatic number: How bad can my greedy heuristic coloring be?

Redundant networks and minimum distance

With the development of economy and society, people have growing demand for healthy living environments. However, there are more than 170,000 old residential communities in China, where aging buildings, old facilities and environmental degradation are common problems that need to be urgently improved. Determining subsidy funding and benefit evaluation is often the blind spot, posing difficulties in government decision-making. In this study, the Fuzzy Delphi Method (FDM) was first adopted to propose a set of standards for outdoor environment renovation of old residential communities in China based on the WELL Community Standard (WCS). On the basis of the I-S model and zero-one integer programming (ZOIP), an optimal decision-making model (ODM) was developed and applied in practical projects. The result showed that ODM can not only help government managers to determine the budget rationally, but also provide a way to promote multiple participations to achieve optimal improvement strategies. It is recommended that ODM should be further expanded on more projects to review and modify the application of ODM in different regions of China.

Computer program for the minimization of development costs for offshore oil and gas fields

ABSTRACT: A versatile computer model for audit-staff scheduling based on a zero-one integer program was presented by Balachandran and Zoltners [1981] (BZ). This paper extends the work of BZ by demonstrating how precedence constraints, due dates, penalty costs, resource leveling, and other audit considerations can be added to the zero-one integer program for audit scheduling. These additional features help improve the realism of the scheduling model, thus making the model more practical for applications.

This paper addresses the issue of optimal allocation of spare modules in complex series-parallel redundant systems in order to achieve a required reliability with minimal cost. To solve this problem, two optimization techniques are considered: Zero-One Integer Programming (01IP) and Quadratic Unconstrained Binary optimization (QUBO). The results are compared with those given by an approximate analytical method based on Lagrange multipliers. For large systems, the numerical results presented show that the 01IP and QUBO methods give better solutions. A comparative time complexity analysis of 01IP and QUBO is also presented.