The solutions used to solve bi-level congestion pricing problems are usually based on heuristic network optimization methods which may not be able to find the best solution for these type of problems. The application of meta-heuristic methods can be seen as viable alternative solutions but so far, it has not received enough attention by researchers in this field. Therefore, the objective of this research was to compare the performance of two metaheuristic algorithms namely, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), with each other and also with a conventional heuristic method in terms of degree of optimization, computation time and the level of imposed Tolls. Hence, a bi-level congestion pricing problem formulation, for simultaneous optimization of Toll Locations and Toll levels on a road network, using these two meta-heuristic methods, was developed. In the upper level of this bi-level problem, the objective was to maximize the variation in the Net Social Surplus (NSS) and in the lower level, the Frank-Wolfe user equilibrium method was used to assign traffic flow to the road network. PSO and GA techniques were used separately to determine the Optimal Toll Locations and levels for a Sioux Falls network. The numerical results obtained for this network showed that GA and PSO demonstrated an almost similar performance in terms of variation in the NSS. However, the PSO technique showed 45% shorter run time and 24% lower mean Toll level and consequently, a better overall performance than GA technique. Nevertheless, the number and Location of Toll links determined by these two methods were identical. Both algorithms also demonstrated a much better overall performance in comparison with a conventional heuristic algorithm. The results indicates the capability and superiority of these methods as viable solutions for application in congestion pricing problems.

The problem of Optimal sensor Location for fault detection in Linear Time-Invariant (LTI) systems is considered. A novel characterization of undetectable faults is shown to give rise to a new Optimal sensor Location problem for fault detection in the presence of L2 disturbances. An algorithm is presented whereby subOptimal solutions to this problem can be determined. A numerical example is presented to illustrate the theory and execution of the algorithm.

The congestion pricing has been discussed as a practical tool for traffic management on urban transport networks. The traffic congestion is defined as an external diseconomy on the network in transport economics. It has been proposed that the congestion pricing would be used to reduce the traffic on the network. This paper investigates the cordon-based second-best congestion-pricing problems on road networks, including Optimal selection of both Toll levels and Toll Locations. A road network is viewed as a directed graph and the cutest concept in graph theory is used to describe the mathematical properties of a Toll cordon by examining the incidence matrix of the network. Maximization of social welfare is sought subject to the elastic-demand traffic equilibrium constraint. A mathematical programming model with mixed (integer and continuous) variables is formulated and solved by use of two genetic algorithms for simultaneous determination of the Toll levels and cordon Location on the networks. The model and algorithm are demonstrated in the road network of Mashhad CBD.

Network Location models comprise one of the main categories of Location models. These models have various applications in regional and urban planning as well as in transportation, distribution, and energy management. In a network Location problem, nodes represent demand points and candidate Locations to locate the facilities. If the links network is unchangeably determined, the problem will be an FLP (Facility Location Problem). However, if links can be added to the network at a reasonable cost, the problem will then be a combination of facility Location and NDP (Network Design Problem). In previous studies, capacity of facilities was considered to be a constraint while capacity of links was not considered at all. The proposed MIP model considers capacity of facilities and links as decision variables. This approach increases the utilization of facilities and links, and prevents the construction of links and facility Locations with low utilization. Furthermore, facility Location cost (link construction cost) in the proposed model is supposed to be a function of the associated facility (link) capacity. Computational experiments as well as sensitivity analyses performed indicate the efficiency of the model.

The purpose of this paper is Optimal Location of distributed generation in electric distribution networks. Load uncertainty and desired voltage range has been modeled using fuzzy data theory. The objective function includes loss reduction, improvement of profile index and voltage stability index with their relevant constraints, voltage constraints and transmittable power from the line. Load variation has been shown for three different time durations (peak, off peak and average).PSO technique has been used to optimize the objective function while Max-Min method has been applied to select the answer. Results produced from the proposed model have been provided in 5 different scenarios on a 33 bus system of IEEE.

Breast cancer is highly prevalent worldwide. Treatment of this disease is a major global public health problem; therefore, numerous studies have explored new molecular profile helping for breast cancer therapy. Different risk factors are attributed to breast cancer; however, chronic inflammation and immune regulation are highly essential. Various molecules impact this context, including Toll-like receptors (TLRs), which are mainly expressed on the membrane of different immune cells and trigger proinflammatory responses. Of note, expressing these receptors, as well as inhibiting their functions lead to different and remarkable results in patients with breast cancer. More specifically, TLRs can induce the apoptosis of cancerous cells, expression of adhesion molecules, metastasis, and cytokine profile change. Therefore, evaluating new therapies and various factors, including demographic characteristics, nutrition, colonized microbial flora, and immune regulatory molecules in breast cancer patients is essential. Such information helps to improve our understanding of this disease and assists scientists to find effective therapies in the future. The content of this article is a review of 128 articles, published in prestigious international journals. Search in Google Scholar, PubMed, Scopus, and Science Direct were conducted using keyword combinations of “ Breast cancer and Toll-like receptor” . This review article is an overview of the role of TLRs in the treatment and progression of breast cancer. According to various research studies, TLRs can significantly affect the progression, metastasis, and treatment of breast cancer.

This paper presents a fuzzy interactive approach to find the Optimal Location of Optimal Unified Power Flow Controller (OUPFC) device as a multi-objective optimization problem. The problem formulation is based on Optimal Power Flow (OPF) problem while the metric function and weighting method are added to ensure the collaboration among objective functions. The objective functions are the total fuel cost, power losses, and system loadability with and without the minimum cost of OUPFC installation. The proposed algorithm is implemented on IEEE 14- and 118-bus systems. The solution procedure uses nonlinear programming with discontinuous derivatives (DNLP) to solve the Optimal Location and settings of OUPFC device to enable power system dispatcher to improve the power system operation. The optimization problem is modeled in General Algebraic Modelling System (GAMS) software using CONOPT solver. Furthermore, the results obtained by OUPFC are compared with those of the Unified Power Flow Controller (UPFC) device. The OUPFC is outperformed by UPFC in the power system operation from the economic and technical point of view.

Purpose: This paper aims to efficiently find the number and Optimal placement of BTSs in the coverage area such that the implementation cost is minimized, while the user's traffic in the corresponding area and the channel interference constraints are satisfied. Design/methodology/approach: An integer linear mathematical model has been proposed to assign all customer points to transceiver-based stations. The objective function has been assumed to minimize fixed costs while considering a penalty for reducing interference. An optimization solver has been applied to solve the model. Findings: The proposed mathematical model was compared to another existing model in the literature from three points of view: coverage cost, construction costs, and running time. The results indicated that the proposed model has the appropriate efficiency to find solutions to real practical problems. In more detail, the proposed model succeeded to find solutions with less coverage or construction cost in a shorter time, compared with the model in literature, which has been referred to as the SSH model in the paper. However, there have been some samples in which the SSH model overtakes the proposed model in one or two mentioned aspects for comparison. Research limitations/implications: The limitation of this study is that the channel model was considered based on the simple free space path loss model, while the real channel model based on the environmental effects can be suggested for future work. Another important issue is that for BTS localization design, knowing the status of the real environment leads to the proper design in such networks. Social/practical implications: BTS localization is the most important issue in mobile networks' design. In a practical situation, there is not any software available to design a mobile network in the corresponding coverage area. Therefore, this paper can help communication engineers to implement the proposed approach in a real environment. Originality/value: In this paper, the problem of the Optimal Location of transceiver-based stations (BTS) in different models in the coverage area has been addressed such that the implementation cost is minimized, while the user's traffic in the corresponding area and the channel interference constraints are satisfied. This has not been considered in the literature. Any of the existing models focus on one aspect to optimize, such as maximizing the coverage, minimizing the interference, and minimizing coverage or construction costs. The novelties of the proposed model are twofold: i) two goals were considered in the objective function, i.e., minimizing construction costs and minimizing interference. Since interference with full coverage is unavoidable, the model added a penalty to the objective function to reduce the interference as much as possible; and ii) it was assumed that there is more than one single type BTS, any of which has different power, radius, and capacity. This makes the model more real and indeed more complicated to solve.