Nur Azriati MatAida Mauziah BenjaminSyariza Abdul-RahmanKu Ruhana Ku-Mahamud...
383-407页
查看更多>>摘要：Solid waste management (SWM) is an important service the government offers to residents of a country to manage generated residual waste. Failure to manage this waste can lead to unpleasant circumstances, such as environmental contamination and outbreaks of pest-borne diseases. Therefore, an efficient and cost-effective SWM system is required to improve the services. This research highlights one of the main issues of the SWM system, which is the waste collection vehicle routing problem (WCVRP). Essentially, this research addresses the adaptation of the plant propagation algorithm (PPA), which has never been considered in prior studies to resolve waste collection problems. The quality of the PPA solution was evaluated in terms of total travel distance, the number of vehicles/drivers required, the total working hours of drivers, and total fuel consumption. The proposed algorithm was tested on a WCVRP benchmark problem. Upon comparing PPA and other best-known solutions depicted in the literature, the solutions achieved on benchmark problems were extremely competitive.
查看更多>>摘要：This paper explores an agent-based model that incorporates the Q-learning algorithm, and this model includes a competitive multi-agent retail-consumer interaction network. In the network model, various retail agents are constructed to compete for consumer groups under different network features (consumer neighbour nodes, consumer network reconnection probability, and consumer herding psychology intensity) with different pricing and service level combinations. All retail agent agents adjust their product prices and service levels under the Q-learning mechanism to maximise their expected sales and profits. Compared to previous studies, we make contributions that include, but are not limited to, constructing consumer networks with nodes of new network characteristics, as well as designing individual consumer characteristics with more complexity, including heterogeneous attributes such as the consumer's income level and the consumer's expectation level. The purpose of this paper is to provide recommendations for selecting the appropriate combination strategies for retailers in a complex market environment.
查看更多>>摘要：Order picking is the most time-consuming and laborious part in warehouse operation. An efficient order batching approach may considerably enhance the effectiveness of the order picking process. In this research, a quadratic programming model is developed to solve the order batching, batch sequencing, and picker routing problems jointly. The objective is to minimise the sum of order processing and tardiness costs for a particular set of customer orders. The model is considered as an NP-hard problem. Therefore, as a solution methodology, a genetic algorithm (GA) based meta-heuristic approach is proposed to solve large-scale problems. A greedy routing technique is also adopted in the GA to estimate the optimal picking sequence for each batch. The effectiveness of the suggested meta-heuristic approach is compared with the earliest due date (EDD) order batching method. The experimental results show that the proposed GA-based approach generates promising results in an acceptable amount of computational time.
Antonio Jose Mendes FerreiraPaulo Jorge de Almeida PereiraMario Jose Batista FrancoDagoberto Ivo Sousa Couto dos Santos...
456-471页
查看更多>>摘要：This study aims to analyse the relation between the determinants of capital structure and the level of debt in small and medium-sized enterprises (SMEs) in the information technology (IT) sector. The methodology adopted consists of applying a questionnaire to 100 IT SMEs in Portugal, followed by descriptive statistical analysis. The results obtained will provide managers and investors with valuable insights, highlighting the importance of factors such as firm size, asset tangibility, growth opportunities, business risk, profitability, age and tax benefits. The conclusion underlines that the relation between firm size and level of debt is complex, depending on contextual factors, and that pecking order theory influences financing decisions. The study fills a gap in the literature and contributes to developing the information technology sector in Portugal. The study refers to the main theories related to capital structure, such as the theory of Durand (1952), the approaches of Modigliani and Miller (1958, 1963), agency theory (Jensen and Meckling, 1976), trade-off theory (Myers, 1984) and pecking order theory (Myers and Majluf, 1984).
查看更多>>摘要：In a modern economy, prospering without credit is difficult. Yet, Geraldes et al. (2022) report, for instance, that as many as 2.5 billion individuals in the world have little to no bank relationships. Referred to as underbanked consumers, they are unable to obtain credit due to their limited or non-existent credit history. Alternative data refers to data sources that are not traditionally used in credit scoring. Current research suggests that alternative data may contain predictive information helpful in assessing the creditworthiness of underbanked consumers. We use statistical and machine learning models to examine the value of alternative data for assessing the creditworthiness of the USA's subprime underbanked consumers. We use a proprietary dataset of automobile loans that includes both traditional and alternative data to compare the predictive value of each data type. Our main finding is that the informational content of alternative data is not subsumed by traditional data. In addition, we find that alternative data alone have value that can help lenders extend credit to subprime underbanked consumers, enabling them to fully participate in the mainstream economy.
查看更多>>摘要：Traditional cold chain logistics vehicles are suitable tor short distance transportation, while long distance cold chain transportation faces more challenges; as the transportation distance increases, the time and temperature control in the cold chain link becomes more difficult. Because the driving route of the vehicle has been subject to the influence of technology, the driving route of the vehicle cannot be optimised. The traditional vehicle transportation is only for the tracking of the vehicle, the infrared sensor avoids obstacles to find the driving route of the vehicle, and the traditional driving route of the vehicle has limitations. At the same time, the genetic algorithm adds an adjustment strategy based on time window, which can effectively reduce the probability of conflict and deadlock, accelerate the convergence speed of the solution, and solve the scheme with the shortest total assembly time within the specified time. Based on the above design, in this paper, the vehicle path optimisation can shorten the transportation time, reduce the overall transportation cost, and improve the transportation efficiency.
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