Simulation-based optimisation using simulated annealing for crew allocation in the precast industry

Numerous different combinations of crew alternatives can be deployed within a labour-intensive manufacturing industry. This can therefore often generate a large number of possible crew allocation plans. However, inappropriate selection of these allocation plans tends to lead to inefficient manufacturing processes and ultimately higher labour allocation costs. Thus, in order to reduce such costs, more allocation systems are required. The main aim of this study is to develop a simulation-based multi-layered simulated annealing system to solve crew allocation problems encountered in labour-intensive parallel repetitive manufacturing processes. The ‘multi-layered’ concept is introduced in response to the problem-solving requirements. As part of the methodology used, a process simulation model is developed to mimic a parallel repetitive processes layout. A simulated annealing module is proposed and embedded into the developed simulation model for a better search for solutions. Also, a multi-layered dynamic mutation operator is developed to add more randomness to the searching mechanism. A real industrial case study of a precast concrete manufacturing system is used to demonstrate the applicability and practicability of the developed system. The proposed system has the potential to produce more cost-effective allocation plans, through reducing process-waiting times as compared with real industrial-based plans

Disruptions in Supply Chain Transportation: A literature review

Efficient and well-organised transportation is crucial to the success of any supply chain operation, but disruptions can occur in competitive and globalised environments, leading to potential damage and interruptions. A thorough literature review on supply chain transportation research is conducted to address these disruptions from a transportation perspective. The objective is to present recent research on various aspects of the transportation problems, address the gap considering disruptions and propose a framework that outlines the factors that may cause transportation disruptions, their relationships, the types of impacts they have, and how they depend on one another

Complex Production-Inventory Replenishment Problem with Uncertainty in Customer Behaviour

A flow-shop production-inventory system can become very complex in terms of production planning and scheduling. One of the causes of complexity in such a system is the uncertainty of customer demand behaviour which disrupts production lines and inventory control. The uncertainty in customer demand behaviour that causes production disruptions can be in the form of order cancellation, change in order delivery sequence and due time. In general, such disruptions cause order shortages, late order delivery, and the underperformance of resources, amongst others. This paper considers the random combination of occurrences of these disruptions under different production scenario problems. An innovative framework that embeds agent-based simulation, heuristic algorithm, and inventory replenishment strategy is proposed to tackle these disruption problems. The integration of these methods formed a robust platform for adapting and accommodating disruptions with minimum impact on production operations. An experimental study is performed, and the results determine the impact of disruptions under different demand and inventory statuses. An inventory replenishment method is compared with sequential and instantaneous replenishment methods to establish the significance of the proposed method

A Constrained Fuzzy Knowledge-Based System for the Management of Container Yard Operations

The management of container yard operations is considered by yard operators to be a very challenging task due to the many uncertainties inherent in such operations. The storage of the containers is one of those operations that require proper management for the efficient utilisation of the yard, requiring rapid retrieval time and a minimum number of re-handlings. The main challenge is when containers of a different size, type, or weight need to be stored in a yard that holds a number of pre-existing containers. This challenge becomes even more complex when the date and time for the departure of the containers are unknown, as is the case when the container is collected by a third-party logistics company without any prior notice being given. The aim of this study is to develop a new system for the management of container yard operations that takes into consideration a number of factors and constraints that occur in a real-life situation. One of these factors is the duration of stay for the topmost containers of each stack, when the containers are stored. Because the duration of stay for containers in a yard varies dynamically over time, an ‘ON/OFF’ strategy is proposed to activate/deactivate the duration of stay factor constraint if the length of stay for these containers varies significantly over time. A number of tools and techniques are utilised for developing the proposed system including: discrete event simulation for the modelling of container storage and retrieval operations, a fuzzy know ledge-based model for the stack allocation of containers, and a heuristic algorithm called ‘neighbourhood’ for the container retrieval operation. Results show that by adopting the proposed ‘ON/OFF’ strategy, 5% of the number of re-handlings, 2.5% of the total retrieval time, 6.6% of the total re-handling time and 42% of the average waiting time per truck are reduced

Industrial occupational risks: application study in renewable energy companies

An organization’s work environment is considered an essential factor in maximizing its value; therefore, a professional work environment ensures higher worker safety and fewer professional accidents by offering offices with suitable environment designs that contribute to maintaining the health and welfare of employees. Therefore, a new conceptual framework is introduced to identify the causes of sudden job accidents and their effect on employees’ safety. This study develops an occupational safety model based on ISO 45001:2018 standards for optimizing the industrial professional work environment that seeks to adopt the Occupational Safety, Health, and Environment standards (OSHE) to reduce work accident risks like industrial companies of renewable energy and sustainability. This model identifies fundamental factors that have a risk level on workers’ lives, which might expose staff lives to death, injury, and disability. These factors include the industrial professional environment, work accidents, current OSHE procedures, and the effectiveness of current health insurance. Based on quantitative analysis methods to evaluate risk-based work accidents, this study proved a significant relationship between the characteristics of the industrial occupational environment in the selected factories and the increase in sudden work accidents. The main suggestion is that industrial company needs to adopt the OSHE ISO45001:2018 standards

Developing an Overbooking Fuzzy-Based Mathematical Optimization Model for Multi-Leg Flights

Overbooking is one of the most vital revenue management practices that is used in the airline industry. Identification of an overbooking level is a challenging task due to the uncertainties associated with external factors, such as demand for tickets, and inappropriate overbooking levels which may cause revenue losses as well as loss of reputation and customer loyalty. Therefore, the aim of this paper is to propose a fuzzy linear programming model and Genetic Algorithms (GAs) to maximize the overall revenue of a large-scale multi-leg flight network by minimizing the number of empty seats and the number of denied passengers. A fuzzy logic technique is used for modeling the fuzzy demand on overbooking flight tickets and a metaheuristics-based GA technique is adopted to solve large-scale multi-leg flights problem. As part of model verification, the proposed GA is applied to solve a small multi-leg flight linear programming model with a fuzzified demand factor. In addition, experimentation with large-scale problems with different input parameters’ settings such as penalty rate, show-up rate and demand level are also conducted to understand the behavior of the developed model. The validation results show that the proposed GA produces almost identical results to those in a small-scale multi-leg flight problem. In addition, the performance of the large-scale multi-leg flight network represented by a number of KPIs including total booking, denied passengers and net-overbooking profit towards changing these input parameters will also be revealed

Agent-Based Modelling and Heuristic Approach for Solving Complex OEM Flow-Shop Productions under Customer Disruptions

The application of the agent-based simulation approach in the flow-shop production environment has recently gained popularity among researchers. The concept of agent and agent functions can help to automate a variety of difficult tasks and assist decision-making in flow-shop production. This is especially so in the large-scale Original Equipment Manufacturing (OEM) industry, which is associated with many uncertainties. Among these are uncertainties in customer demand requirements that create disruptions that impact production planning and scheduling, hence, making it difficult to satisfy demand in due time, in the right order delivery sequence, and in the right item quantities. It is however important to devise means of adapting to these inevitable disruptive problems by accommodating them while minimising the impact on production performance and customer satisfaction. In this paper, an innovative embedded agent-based Production Disruption Inventory-Replenishment (PDIR) framework, which includes a novel adaptive heuristic algorithm and inventory replenishment strategy which is proposed to tackle the disruption problems. The capabilities and functionalities of agents are utilised to simulate the flow-shop production environment and aid learning and decision making. In practice, the proposed approach is implemented through a set of experiments conducted as a case study of an automobile parts facility for a real-life large-scale OEM. The results are presented in term of Key Performance Indicators (KPIs), such as the number of late/unsatisfied orders, to determine the effectiveness of the proposed approach. The results reveal a minimum number of late/unsatisfied orders, when compared with other approaches

A System Based on Fuzzy Logic to Manage Operations in Container Yards

This article focuses on the assignment of arrived containers to pre-existing stacks stored in one of the container yards, particularly when the containers' date of departure and time are unknown. This becomes more difficult when different-sized, typed, and weighted containers needs be stored in pre-existing containers yard. The main objective is to create a Fuzzy Knowledge-Based System (FKB_CYM) that considers practical factors and limitations such as container quantity per stack and customer, type, size, and weight. Various tools and methodologies are used, including Discrete Event (DE), Fuzzy Knowledge-Based Modelling (FKBM), and a Neighborhood Algorithm (NA). The paper thoroughly discusses and evaluates the system's findings

Navigating the Digital Landscape:How E-Marketing and Product Attractiveness Shape Company Reputation from a Customer-Centric Perspective

Purpose – This study investigates the influence of e-marketing risks on a Corporation’s Reputation (CR) resulting from its online marketing of products and services. Design/methodology/approach – A comprehensive analysis was conducted to enhance the company’s e-marketing strategies and bolster its reputation in the market. This involved an investigation into key factors of e-marketing risks, such as customer confidence, product quality, marketing fraud, credibility and customer knowledge and proficiency in using online platforms. These factors have directly impacted the company’s reputation, including aspects such as product/service quality, attractiveness, performance and commitment to social responsibility. Findings – Its finding indicates that customers’ lack of confidence in e-marketing has a strong impact on CR, followed by product quality and credibility. The absence of consumer awareness about e-marketing websites and e-fraud frequently negatively affects the organizational reputation. Practical implications – To enhance the corporation’s reputation, it is recommended that companies provide educational resources on online shopping, including guidance on using the company’s website, comparing prices and other services that facilitate online purchases. This will help to support the credibility of e-marketing and enhance customer trust. Originality/value – This research is an exploration of how e-marketing has affected a Corporation’s Reputation. It provides modern knowledge about the dynamic interplay between digital strategies and brand perception. Investigating this relationship provides valuable insights into the evolving landscape of consumer trust in the digital age. By analysing the various ways in which e-marketing influences a company’s reputation, innovative approaches can be developed to enhance its online presence and build lasting customer trust