A Genetic Algorithm with Quantum Random Number Generator for Solving the Pollution-Routing Problem in Sustainable Logistics Management

Background: The logistics network design with cross-docking operations enables shipping service providers to integrate the physical flow of products between vendors and dealers in logistics management. The collective goal is to synchronize the goods in both pickup and delivery operations concurrently to reduce the handling cost, inventory cost, and operation cost generated. Therefore, the optimal vehicle routing plan is crucial to generate a truck routing schedule with minimal total cost, fulfilling the purchasing requirements and the distribution demand. Global warming and climate change are important topics due to increasing greenhouse gas emissions. Sustainable logistics management with optimized routes for trucks can assist in reducing greenhouse gas emissions and easing the effects of temperature increases on our living environment. Methods: A heuristic approach based on Particle Swarm Optimization, called ePSO, was proposed and implemented in this paper to solve the vehicle routing problems with cross-docking and carbon emissions reduction at the same time. Results: Performance comparisons were made with the Genetic Algorithm (GA) through the experiments of several vehicle routing problems with pickup and delivery benchmark problems to validate the performance of the ePSO procedure. Conclusions: Experimental results showed that the proposed ePSO approach was better than the GA for most cases by statistical hypothesis testing.

Aims: This study proposes a bi-objective linear integer programming model for heterogeneous fleet VAP with emissions considerations. Profit maximization and emissions minimization objectives are employed to handle economic and environmental sustainability purposes. Background: Our literature survey shows that there is no model for the heterogeneous fleet VAP with emissions considerations that simultaneously consider vehicle heterogeneity, penalty costs for unmet demands, and emissions from transportation operations. Objective: The model is employed to also make several scenario analyses on sustainable freight logistics management to understand the trade-offs among economic and environmental objectives. In freight transportation problems, decision-makers need to be able to maintain profitability and to reduce emissions. Methods: In this study, a bi-objective linear integer programming model is proposed for a heterogeneous fleet Vehicle Allocation Problem (VAP) with emissions considerations encountered in the field of sustainable freight transportation. Results: In the numerical analyses, various practical assumptions that can be confronted by decision-makers in real life are discussed. In each analysis, total profit and emissions amounts are revealed along with several other KPIs. The results of the analyses provided in this study could also be useful in terms of understanding the relations among pillars of sustainability in VAPs. Conclusion: It is thought that the proposed model has the potential to aid decision-making processes in sustainable logistics management. In the base case analyses, the total profit obtained under profit maximization is about nine times higher than that obtained under emissions minimization. When the aim is to minimize emissions, the total emissions are found to be nearly one-tenth of that of profit maximization. Supported by also additional scenario analyses, it can be concluded that it might not economically viable to be environmentally-friendly for companies. Therefore, companies have to be encouraged or forced to take environmentally and socially responsible actions through legislation. The analyses demonstrated that various legislative policies on emissions may affect the transportation plans differently in such vehicle allocation systems.

Random numbers generated by pseudo-random and true random number generators (TRNG), are used in a wide variety of applications. A TRNG relies on a nondeterministic source to produce random numbers. In this paper, we develop a TRNG using a heuristic evolutionary algorithm together with signal processing techniques. Our proposed algorithm consists of three phases:(i) Extraction: where a noise source(such as race conditions during concurrent memory accesses on a GPU) is sampled into random numbers, (ii) Exact Histogram Equalization: takes the output from (i) and delivers a specified output distribution, (iii) Stationarity Enforcement: using a genetic algorithm, the output of (ii) is permuted until the random numbers meet wide sense stationarity within a specified quality defined by Gaussian distribution with the expected standard deviation on the power spectral density of random numbers. We propose guideline parameters for the evolutionary algorithm to ensure fast convergence, within the first 100 generations, with a standard deviation over the specified quality level of less than 0.02.

Random numbers generated by pseudo-random and true random number generators (TRNG) are used in a wide variety of important applications. A TRNG relies on a non-deterministic source to sample random numbers. In this paper, we improve the post-processing stage of TRNGs using a heuristic evolutionary algorithm. Our post-processing algorithm decomposes the problem of improving the quality of random numbers into two phases: (i) Exact Histogram Equalization: it modifies the random numbers distribution with a specified output distribution; (ii) Stationarity Enforcement: using genetic algorithms, the output of (ii) is permuted until the random numbers meet wide-sense stationarity. We ensure that the quality of the numbers generated from the genetic algorithm is within a specified level of error defined by the user. We parallelize the genetic algorithm for improved performance. The post-processing is based on the power spectral density of the generated numbers used as a metric. We propose guideline parameters for the evolutionary algorithm to ensure fast convergence, within the first 100 generations, with a standard deviation over the specified quality level of less than 0.45. We also include a TestU01 evaluation over the random numbers generated.

A true random number generator (TRNG) is suitable for generating secure keys and nonces. TRNGs implemented in IoT devices must be small in scale and have low power consumption. The random number sequence generated by TRNG needs to have high entropy immediately after startup and a stable state. In this paper, three types of ring oscillator type TRNGs, TERO-based, COSO-based, and STR-based TRNG, are implemented on Zynq-7010. When these TRNGs are implemented as a single entropy source, it is challenging to implement them because it is necessary to evaluate the layout and wiring for each FPGA. This paper proposes a TRNG configuration, which exclusively ORs the outputs of multiple entropy sources. We show that this configuration can reduce the implementing difficulty and realize high entropy. For the random number sequence evaluation, we use the statistical test of NIST SP800-90B and BSI AIS 20/31. In addition, the random number sequence immediately after the startup is also statistically evaluated. As a result, our proposed TRNGs generate high entropy random numbers and are easy to implement on FPGA when we implement TRNGs with eight single entropy sources for TERO-based TRNG, 48 for COSO-based TRNG, and two for STR-based TRNG, respectively.

Exploiting Random Chemistry for Digital Security

Random numbers are at the heart of diverse fields, ranging from simulations of stochastic processes to classical and quantum cryptography. The requirement for true randomness in these applications has motivated various proposals for generating random numbers based on the inherent randomness of quantum systems. The generation of true random numbers with arbitrarily defined probability distributions is highly desirable for applications, but it is very challenging. Here we show that single-photon quantum walks can generate multi-bit random numbers with on-demand probability distributions, when the required “coin” parameters are found with the gradient descent (GD) algorithm. Our theoretical and experimental results exhibit high fidelity for various selected distributions. This GD-enhanced single-photon system provides a convenient way for building flexible and reliable quantum random number generators. Multi-bit random numbers are a necessary resource for high-dimensional quantum key distribution.

The subject matter of the article is pseudo-random number generators. Random numbers play the important role in cryptography. Using not secure pseudo-random number generators is a very common weakness. It is also a fundamental resource in science and engineering. There are algorithmically generated numbers that are similar to random distributions but are not random, called pseudo-random number generators. In many cases the tasks to be solved are based on the unpredictability of random numbers, which cannot be guaranteed in the case of pseudo-random number generators, true randomness is required. In such situations, we use real random number generators whose source of randomness is unpredictable random events. Quantum Random Number Generators (QRNGs) generate real random numbers based on the inherent randomness of quantum measurements. The goal is to develop a mathematical model of the generator, which generates fast random numbers at a lower cost. At the same time, a high level of randomness is essential. Through quantum mechanics, we can obtain true numbers using the unpredictable behavior of a photon, which is the basis of many modern cryptographic protocols. It is essential to trust cryptographic random number generators to generate only true random numbers. This is why certification methods are needed which will check both the operation of the device and the quality of the random bits generated. The goal of the research is also to develop the model of a hybrid semi self-testing certification method for quantum random number generators (QRNG). The tasks to be solved are to create the mathematical model of a random number generator, which generates the fast random numbers at a lower cost. To create the mathematical model of a hybrid semi self-testing certification method for quantum random number generators. To integrate a hybrid semi self-testing certification method to the hybrid random number generator. the methods used are mathematical optimization and simulation. The following results were obtained: we present the improved hybrid quantum random number generator, which is based on QRNG, which uses the time of arrival of photons. The model of a hybrid semi self-testing certification method for quantum random number generators (QRNG) is offered in the paper. This method combines different types of certification approaches and is rather secure and efficient. Finally, the hybrid certification method is integrated into the model of the new quantum random number generator. Conclusions. The scientific novelty of the results obtained is as follows: 1. The hybrid quantum random number generator is offered, which is based on QRNG, which uses the time of the arrival of photons. It uses the simple version of the detectors with few requirements. The hybrid QRNG produces more than one random bit per the detection of each photon. It is rather efficient and has a high level of randomness. 2. The hybrid semi self-testing certification method for quantum random number generators (QRNG) is offered. The Self-testing, as well as device-independent quantum random number generation methods, are analyzed. The advantages and disadvantages of both methods are identified. Based on the result the hybrid method is offered. 3. The hybrid semi self-testing certification method for quantum random number generators is integrated into the offered model of the quantum random number generator. The paper analyzes its security and efficiency. The paper offers to use the new random number generator in the crypto-schemes.

Data encryption is a way to increase security of data by using cryptographic keys generated from random numbers. Random Number generator (RNG), which produces such numbers, is classified as True Random Number Generator (TRNG) or Pseudorandom Number generator (PRNG). The first one uses physical phenomena to generate random numbers whereas the second one uses deterministic systems. A commonly used deterministic system in PRNG applications is the logistic map, a nonlinear system that under certain operating ranges becomes chaotic. However, the logistic map alone does not generate satisfactory random sequence because the sequence generated is not uniformly distributed, and it does not have good results in statistical tests, such as the NIST test suite. To solve this problem, this paper proposes an implementation in Field Programmable Gate Array (FPGA) of a PRNG, which uses the k – logistic map concept, discarding the most significant k decimal digits of an underlying orbit generated from the traditional logistic map equation. The results from synthesis and simulations show that the designed circuit is a low-cost and a high efficiency RNG solution.

The fast evolution of sustainability leads to the development of a new fast-growing concept called sustainable logistics management. This research addresses recent business trends and challenges in logistics and their implications for sustainable logistics management. Additionally, we discuss policy and research developments in resource-efficient logistics and present several practice examples in sustainable logistics management from transportation business companies. The conducted research on relevant literature and sustainability reports of several leading logistics companies shows that the logistics sector is committed to sustainable development and continually looks for ways to be environmentally and socially responsible and more efficient right across the organizations.

As the number of IoT devices increases, security is one of the critical factors. Since random numbers are used to generate nonce and encryption keys, degradation of the randomness generated by TRNGs (True Random Number Generators) causes damage to system security. Several attacks have been proposed to reduce the randomness of the TRNG by changing the operating conditions, such as frequency injection, glitch impact, temperature change, and power supply voltage manipulation. In addition, the side-channel attack against TRNG is proposed to predict the random number output. This paper evaluates temperature variation and proposes side-channel attacks against COSO-based TRNG (coherent sampling ring oscillator-based TRNG). The results show that the temperature variation does not affect the randomness of the TRNG under the temperature range of 0°C to 80°C. On the other hand, the side-channel attack correctly read the random output numbers in 97.9 % of the cases. Note that the target circuit was connected to the output pin and side channel information was obtained from it. We propose two countermeasures against the side-channel attacks and demonstrate their effectiveness.

Dr Zhang Yixin of Nanjing University, China, talks about the work behind the paper ‘Portable true random number generator for personal encryption application based on smartphone camera’, page 1841. Dr Zhang Yixin My major was more related to radio communication as an undergraduate. About eight years ago, I started a PhD at Nanjing University, that was the beginning of my research in optical. In 2011, I joined NTRC at Nanyang Technological University in Singapore as a postdoctoral research fellow. The lab had just begun a joint military project on unconditional encrypted optical communication. That is where my current research work really began. Two years later I returned to Nanjing University as a lecturer and my current main field of research is single photon level optical signal detection and its applications, such as the true random number generator (TRNG) based on photon distribution. True random numbers are the key to secure communication, even if quantum technology is included. A TRNG based on an off-the-shelf image sensor, rather than a thousands-of-dollars photon counter, would be much more attractive for portable personal encryption applications, such as E-payment, privacy call and cryptographic data transmission on a smartphone or laptop. In the near future, the security level of personal devices has to be enhanced with new encryption technology to stand against the technological advances of eavesdroppers; this is the goal of our current project. Present TRNGs are mainly based on specialised, expensive hardware like single photon detectors, chaotic lasers and radioactive nuclei, which are more suited to commercial or academic applications than personal usage. We present a portable TRNG configuration simply based on the camera of a smartphone. The randomness of the output bit sequence has been proved with NIST tests, and all necessary processing functions could be fully integrated within Android software in the near future. This approach offers a promising solution for portable personal encryption, since no equipment is needed except the smartphone itself. Back in my PhD days, working on micro-structure imaging, our group confirmed by experiment that in certain conditions, shot noise other than thermal noise can dominate the overall noise characteristics of a high-sensitivity CCD image sensor. Commonly speaking, shot noise of photocurrent is believed to be a quantum process and true random number could be generated accordingly. However, the performance of image sensors on smartphones were not as good then. Two or three years later, I saw a picture taken by my colleague's latest phone, and thought maybe it was time to realise the portable TRNG with smartphone camera. I see two main trends in recent TRNG research. The first is realising higher bit rates; speeds of gigabits per second were reported several years ago. The second is looking for new physical random phenomena that are more reliable. Arguments have always existed on whether chaotic process is as random as quantum process. However, I believe that the integration of TRNGs is very likely to be the main topic in the future. TRNGs are still too big and expensive for most practical applications. Integration of optics and electronics components on a single chip is necessary for portable and low-cost TRNGs. Meanwhile, TRNGs only solve the random number generation problem, a communication protocol which employs true random numbers as secret keys for encryption also needs to be developed. Here at the Institute of Optical Communication Engineering at Nanjing, my group will try to improve the Android App for TRNGs to automatically adapt to different types of smartphone, since the camera setting is essential to the overall performance of output random bits. We are also working on high-speed single photon counting technology based on avalanche photodiodes to improve the detection speed if higher rates are required. Another research area we are involved in is fibre optical sensing, with the goal of locating eavesdroppers in time, while they are intercepting optical signals from fibre communication links. Probe pulse coding based on TRNGs will be used for the improvement of measuring speed, spatial resolution and dynamic range.

The basis of encryption techniques is random number generators (RNGs). The application areas of cryptology are increasing in number due to continuously developing technology, so the need for RNGs is increasing rapidly, too. RNGs can be divided into two categories as pseudorandom number generator (PRNGs) and true random number generator (TRNGs). TRNGs are systems that use unpredictable and uncontrollable entropy sources and generate random numbers. During the design of TRNGs, while analog signals belonging to the used entropy sources are being converted to digital data, generally comparators, flip-flops, Schmitt triggers, and ADCs are used. In this study, a computer-controlled new and flexible platform to find the most appropriate system parameters in ADC-based TRNG designs is designed and realized. As a sample application with this new platform, six different TRNGs that use three different outputs of Zhongtang, which is a continuous time chaotic system, as an entropy source are designed. Random number series generated with the six designed TRNGs are put through the NIST800–22 test, which has the internationally highest standards, and they pass all tests. With the help of the new platform designed, ADC-based high-quality TRNGs can be developed fast and also without the need for expertise. The platform has been designed to decide which entropy source and parameter are better by comparing them before complex embedded TRNG designs. In addition, this platform can be used for educational purposes to explain how to work an ADC-based TRNG. That is why it can be utilized as an experiment set in engineering education, as well.

The object of research is the process of mutual synchronization of quantum random number generators (QRNG) in the group standard of quantum noise. A method for generating random numbers is proposed, which relates to the methods of group standardization of the QRNG, and is used to increase the speed and reliability of the random number formation The paper substantiates the mathematical model of quantum phase noise of the QRNG group, which are in a mutual synchronization mode. The method is based on solving the problem of identifying parameters of a group of the same type to the QRNG in the mutual synchronization mode. The solution to this problem requires the availability of reliable and operational data when calculating the Kalman filter parameters necessary for estimating the synchronization parameters of quantum measures of phase noise. The results of experimental studies presented in the article are an example of building a QRNG with a given level of reliability and speed. A feature of the proposed QRNG quantum phase noise measurement system is the synchronization of processing time using GPS signals (Ll C/A).

True random number generators (TRNGs) based on ring oscillators are employed in many devices because they can be constructed with logic gates only. Random numbers generated by TRNGs are used for various cryptographic systems as session keys, nonces, and masks. The randomness of a TRNG is characterized by uniformity, nonreproducibility, and unpredictability. Moreover, the quality of random numbers affects cryptographic systems. In particular, degradation of the unpredictability can reduce the security of the cryptographic system because random numbers can be easily estimated. Side-channel attacks, which exploit additional information leaked from a cryptographic module to reveal secret information, are well known. If some additional information reflecting the output bit can be measured from electromagnetic (EM) emission as a side-channel leakage against a TRNG, the unpredictability of the TRNG may decrease. Accordingly, this article introduces the leakage model that reflects an output bit generated by a transition effect ring oscillator (TERO) based TRNG, and an attack that estimates random number bits by measuring EM emission from an integrated circuit against TERO-based TRNG. We propose a leakage model against a TERO-based TRNG and demonstrate that the output bits of the TRNG can be estimated by analyzing the radiated emissions. We also consider a countermeasure against the proposed attack.