A new two-stage nurse scheduling approach based on occupational justice considering assurance attendance in works shifts by using Z-number method: A real case study

In this paper, a new binary integer programming mathematical model for scheduling nurses' problems in the emergency department of Kamkar Hospital in Qom province is developed. The manual arrangement of nurses by the head nurse and its time-consuming, occasional absences during the period and protests against injustices in the arrangement of nurses' work shifts were among the emergency department's challenges before implementing the model. Most relevant studies aimed to enhance nurses' satisfaction by creating a general balance considering occupational preferences. Thus, the present study pursued justice through considering preferences based on the results from periodical evaluations of each nurse's performance with the ultimate goal of improving nurses' satisfaction. Moreover, the lack of clarity in selecting shifts, which may cause irregular attendance, was improved using the Z-number method. After the run of the model, the rate of nurses' absences decreased by 40%, the rate of complaints about the performance of the nursing unit decreased by 50%. Also, nurses' satisfaction increased by 30% after the implementation of the model.

Optimal path discovery for two moving sinks with a common junction in a wireless sensor network

A new algorithm is described for determining the optimal round-trip paths for two moving sinks in a wireless sensor network. The algorithm uses binary integer programming to select two non-overlapping shortest paths except having a common junction node to cover all the sensor nodes. The two paths are balanced as nearly equal as possible. That is the sensor nodes along each path are equal or differ by just one depending on whether the total number of sensor nodes excluding the junction node is even or odd. In this method, both the path lengths are made equal or very nearly equal while the total length is minimized. This integrated approach is a novel and unique solution to solve the dual moving sink path problem in a wireless sensor network.

A Binary Integer Programming Method for Optimal Wind Turbines Allocation

The present study introduces a Binary Integer Programming (BIP) method to minimize the number of wind turbines needed to be installed in a wind farm. The locations of wind turbines are selected in a virtual grid which is constructed considering a minimum distance between the wind turbines to avoid the wake effect. Additional equality constraints are also included to the proposed formulation to prohibit or enforce the installation of wind turbines placement at specific locations of the wind farmland. Moreover, a microscopic wind turbine placement considering the local air density is studied. To verify the efficiency of this proposal, a square site was subdivided into 25 square cells providing a virtual grid with 36 candidate placement locations. Moreover, a virtual grid with 121 vertices related with a Greek island is also tested. All simulations conducted considering the area of geographical territory, the length of wind turbine blades, as well as the capacity of each turbine.

Data envelopment analysis using the binary-data

Purpose The purpose of this paper is to propose the data envelopment analysis (DEA) model that can be used as binary-valued data. Often the basic DEA models were developed by assuming that all of the data are non-negative. However, there are situations where all data are binary. As an example, the information on many diseases in health care is binary data. The existence of binary data in traditional DEA models may change the behavior of the production possibility set (PPS). This study defines a binary summation operator, expresses the modified principles and introduces the extracted PPS of axioms. Furthermore, this study proposes a binary integer programming of DEA (BIP-DEA) for assessing the efficiency scores to use as an alternate tool in prediction. Design/methodology/approach In this study, the extracted PPS of modified axioms and the BIP-DEA model for assessing the efficiency score is proposed. Findings The binary integer model was proposed to eliminate the challenges of the binary-value data in DEA. Originality/value The importance of the proposed model for many fields including the health-care industry is that it can predict the occurrence or non-occurrence of the events, using binary data. This model has been applied to evaluate the most important risk factors for stroke disease and mechanical disorders. The targets set by this model can help to diagnose earlier the disease and increase the patients’ chances of recovery.

Binary Integer Programming Approach to Optimal Content Placement in Cloud-based Content Delivery Networks

Over the last decades, Content Delivery Networks (CDNs) have been developed to overcome the limitation of user perceived latency by replicating contents from origin server to its content servers around the globe close to clients. As some contents occupy most of the storage capacity and processing power in traditional private content servers, cloud computing can provide a pool of storage and processing power resources for caching contents. By adopting cloud computing to CDN, the content provider can use the cloud infrastructure by distributing the contents to cloud servers which will then deliver to near clients. In this paper, we propose a cloud-based CDN framework designed by two schemes 1) UDP/TCP-based content distribution from origin server to cloud servers and 2) SDN-based cloud server coordination. In addition, we also formulate the optimal content placement problem using binary integer programming to minimize the total cost of renting resources including storage, processing power, and network bandwidth in cloud providers for hosting contents from origin server. Then, the optimal solution obtained from binary integer programming is evaluated by greedy algorithm and simulations. The proposed framework helps content provider to offer high quality of services to clients while minimizing the cost of rented cloud resources.

Reshuffle minimisation to improve storage yard operations efficiency

There are many ways to measure the efficiency of the storage area management in container terminals. These include minimising the need for container reshuffle especially at the yard level. In this paper, we consider the container reshuffle problem for stacking and retrieving containers. The problem was represented as a binary integer programming model and solved exactly. However, the exact method was not able to return results for large instances. We therefore considered a heuristic approach. A number of heuristics were implemented and compared on static and dynamic reshuffle problems including four new heuristics introduced here. Since heuristics are known to be instance dependent, we proposed a compatibility test to evaluate how well they work when combined to solve a reshuffle problem. Computational results of our methods on realistic instances are reported to be competitive and satisfactory.

Optimization of The Best Line-up in Football using Binary Integer Programming Model

This paper aims to find the formation with the best line-up of the Liverpool FC football team in the English Premier League in the 2020/2021 season. Researchers used binary integer programming (BIP) modeling to determine optimum solutions. The data used for this optimization is the rating value of the players recorded in the performance data from the previous matches. The optimum result of this problem is the selection of variables that are valued at 1, namely {x_1, x_4, x_6, x_8, x_21, x_28, x_34, x_37, and x_39} for formations 4-3-3 with a maximum value of 82.47, and variables {x_1, x_6, x_7, x_8, x_11, x_14, x_16, x_29, x_31, x_32, andx_42} for 4-2-3-1 formations with a maximum value of 80.04. The 4-3-3 formation is more effective because it has a higher maximum rating than the 4-2-3-1 formation. 4-3-3 formation is an attacking formation with a higher intensity of attack and faster than 4-2-3-1 formation that tends to defend moderately.

Optimization of The Best Line-up in Football using Binary Integer Programming Model

This paper aims to find the formation with the best line-up of the Liverpool FC football team in the English Premier League in the 2020/2021 season. Researchers used binary integer programming (BIP) modeling to determine optimum solutions. The data used for this optimization is the rating value of the players recorded in the performance data from the previous matches. The optimum result of this problem is the selection of variables that are valued at 1, namely {𝑥1,𝑥4,𝑥6,𝑥8,𝑥11,𝑥18,𝑥21,𝑥28,𝑥34,𝑥37,dan 𝑥39 } for formations 4-3-3 with a maximum value of 82.47, and variables {𝑥1,𝑥6,𝑥7,𝑥8,𝑥11,𝑥14,𝑥16,𝑥29,𝑥31,𝑥32, dan 𝑥42 } for 4-2-3-1 formations with a maximum value of 80.04. The 4-3-3 formation is more effective because it has a higher maximum rating than the 4-2-3-1 formation. 4-3-3 formation is an attacking formation with a higher intensity of attack and faster than 4-2-3-1 formation that tends to defend moderately.