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This paper, considers the multi-depot vehicle routing problem with time window considering two repair and pickup vehicles (CMDVRPTW).

The objective of this problem is minimization of the total traveling cost and the time window violations. Two meta-heuristic algorithms, namely, simple genetic algorithm (GA) and hybrid genetic algorithm (HGA) are used to find the best solution for this problem. A comparison on the results of these two algorithms has been done and based on the outcome, it has been proved that HGA has better performance than GA.

A comparison on the results of these two algorithms has been done and based on the outcome, it has been proved that HGA has better performance than GA.

This paper, considers the multi-depot vehicle routing problem with time window considering two repair and pickup vehicles (CMDVRPTW). The defined problem is a practical problem in the supply management and logistic. The repair vehicle services the customers who have goods, while the pickup vehicle visits the customer with nonrepaired goods. All the vehicles belong to an internal fleet of a company and have different capacities and fixed/variable cost. Moreover, vehicles have different limitations in their time of traveling. The objective of this problem is minimization of the total traveling cost and the time window violations. Two meta-heuristic algorithms (simple genetic algorithm and hybrid one) are used to find the best solution for this problem.

This research was prompted by work undertaken by the author on the efficiency of shipping operations in the Suez Canal. The physical limitations of the Canal allow only one-way movement of ships for the greater part of its length, and thus ships are organised in convoys. These convoys have fixed starting times, with normally just one convoy per day operating in each direction. When traffic is heavy in the southbound direction, a second (smaller) relief convoy is organised to reduce waiting times which can otherwise exceed 24 hours. The process can be analysed by means of a bulk-service queueing model, where convoys of ships correspond to service batches of customers.

The model has application in the many other fields of transport where relief services are supplied. For example, a coach or train operator will often provide a relief service when customer demand is high. The process may be extended to cover cases where relief is provided for the relief service, resulting in a “cascade” of relief service queues.

In line with computational technological advances, obtaining optimal solutions for engineering problems has become attractive research topics in various disciplines and real engineering systems having multiple objectives. Therefore, it is aimed to ensure that the multiple objectives are simultaneously optimized by considering them among the trade-offs. Furthermore, the practical means of solving those problems are principally concentrated on handling various complicated constraints. The purpose of this paper is to suggest an algorithm based on symbiotic organisms search (SOS), which mimics the symbiotic reciprocal influence scheme adopted by organisms to live on and breed within the ecosystem, for constrained multi-objective engineering design problems.

Though the general performance of SOS algorithm was previously well demonstrated for ordinary single objective optimization problems, its efficacy on multi-objective real engineering problems will be decisive about the performance. The SOS algorithm is, hence, implemented to obtain the optimal solutions of challengingly constrained multi-objective engineering design problems using the Pareto optimality concept.

Four well-known mixed constrained multi-objective engineering design problems and a real-world complex constrained multilayer dielectric filter design problem are tackled to demonstrate the precision and stability of the multi-objective SOS (MOSOS) algorithm. Also, the comparison of the obtained results with some other well-known metaheuristics illustrates the validity and robustness of the proposed algorithm.

The algorithmic performance of the MOSOS on the challengingly constrained multi-objective multidisciplinary engineering design problems with constraint-handling approach is successfully demonstrated with respect to the obtained outperforming final optimal designs.

Agriculture and associated services are central to the rural economy of the United Kingdom. Rural veterinary enterprises are important providers of services to livestock producers, but are now facing concerns over their future economic viability. The objectives of this chapter are to outline the changes occurring in the veterinary and agricultural sectors, and to explore the main issues affecting veterinary enterprises in a changing business environment.

This is a conceptual chapter contextualised mainly within the United Kingdom. As such, the methodological approach comprises a critical review of current academic literatures, as well as government reports and relevant media articles.

The findings demonstrate that the commercial success of rural veterinary enterprises is critical to ensuring the future provision of high-quality animal health services to both farmers and government. The current issues facing farmers are likely to affect their willingness and resources to invest in veterinary services. Furthermore, farmers may have doubts as to vets’ ability to provide business-focussed services that add value. In addition, many public services are outsourced to private veterinary enterprises, and forthcoming policy changes are expected to lead to reduced income from public sources for both vets and their livestock farming clients. While wider issues affecting agriculture are beyond the control of private veterinary practitioners, veterinary enterprises will need to ensure that they can deal with such challenges and, where required, adapt their services accordingly.

The chapter is based on a review of extant literatures, and the scope of the research is therefore limited to existing knowledge about the farm animal veterinary business landscape.

The chapter summarises current knowledge of the challenges facing rural veterinary enterprises. While some of the issues described are specific to the veterinary sector, many are also relevant to other rural SMEs providing knowledge-intensive services to farmers. The chapter also describes areas requiring further empirical research.

The vehicle routing problem (VRP) has been widely investigated during last decades to reduce logistics costs and improve service level. In addition, many researchers have realized the importance of green logistic system design in decreasing environmental pollution and achieving sustainable development.

In this paper, a bi-objective mathematical model is developed for the capacitated electric VRP with time windows and partial recharge. The first objective deals with minimizing the route to reduce the costs related to vehicles, while the second objective minimizes the delay of arrival vehicles to depots based on the soft time window. A hybrid metaheuristic algorithm including non-dominated sorting genetic algorithm (NSGA-II) and teaching-learning-based optimization (TLBO), called NSGA-II-TLBO, is proposed for solving this problem. The Taguchi method is used to adjust the parameters of algorithms. Several numerical instances in different sizes are solved and the performance of the proposed algorithm is compared to NSGA-II and multi-objective simulated annealing (MOSA) as two well-known algorithms based on the five indexes including time, mean ideal distance (MID), diversity, spacing and the Rate of Achievement to two objectives Simultaneously (RAS).

The results demonstrate that the hybrid algorithm outperforms terms of spacing and RAS indexes with p-value <0.04. However, MOSA and NSGA-II algorithms have better performance in terms of central processing unit (CPU) time index. In addition, there is no meaningful difference between the algorithms in terms of MID and diversity indexes. Finally, the impacts of changing the parameters of the model on the results are investigated by performing sensitivity analysis.

In this research, an environment-friendly transportation system is addressed by presenting a bi-objective mathematical model for the routing problem of an electric capacitated vehicle considering the time windows with the possibility of recharging.

Presents an overview of the field of genetic algorithms, pioneered in the field of natural adaptive systems and simulated in software. They are shown as representing a novel optimization strategy which is receiving much attention. In machine learning they are a component of classifier systems which are able to extract rules from data. The algorithms discussed are based on the principles of population genetics and biology.

The Milk and Dairies (Scotland) Order, 1925.—This Order, framed under Section 12 of the Act, and applying to Scotland as a whole, was issued along with the model dairy byelaws. It prescribed the form of register of dairies and dairymen, and contained provisions for the ascertainment of infectious disease at dairies, for the prevention of contamination of milk at railway stations, on the street, by means of unsuitable conveyances or unsuitable surroundings, or through insulticient protection from dust or exposure. The colouring or thickening of cream was prohibited by the Order; me use of wooden vessels, except for buttermilk, was prohibited; milk vessels for transit were required to nave marked on them the name and address of the owner, to have a proper lid, and to be locked or sealed. The Order also filled a gap in the administrative provisions of the Act by requiring every person about a dairy, if he became aware that any person in his household was suffering from an infectious disease, to notify the dairyman immediately. The dairyman must then notify the medical officer of health.

This chapter focuses on the orientation towards the medical profession shown by 18-year-old Sardinian students who were asked to write in an essay how they imagined their future. Interest in the medical profession opens up interesting views on what this path may represent for young people given the current general climate of work uncertainty. This chapter focuses on students’ career narratives and, in particular, on their perceived difficulties in accessing medical studies and on the reasons this profession appears so attractive to them. Medicine is, in fact, constructed as a solid, gendered professional path, with a clear vocation career-wise, and it is kept safe from the increasing uncertainty of the labour market. Further, a career in medicine is easy to imagine because there are several medical TV series. Third, the concept of medicine is embedded with positive values and care-centred attitudes, and it therefore ‘sounds good’. The specific ways in which these orientations are gendered are discussed.