This paper addresses a vehicle scheduling problem encountered in the cold chain logistics of the frozen food delivery industry. Unlike the single product delivery scenario, we propose an optimization model that manages the delivery of a variety of products. In this scenario, a set of customers make requests for a variety of frozen foods which are being loaded together. The objective is to find the routes that represent the minimum delivery cost for a fleet of identical vehicles that, departing from a depot, visiting all customers only once and returning to the depot. The delivery cost includes the transportation cost, the cost of refrigeration, the penalty cost and cargo damage cost based on the characteristics of different frozen food products. Apart from the usual constraints of time windows and loading weight, the study also takes into account the constraints of loading volume related to the unit volume of different frozen foods. We then propose a Genetic Algorithm (GA) method for the model. Computational tests with real data from a case validate the feasibility and rationality of the model and show the efficient combinations of parameter values of the GA method.

We consider perishable inventory control with freshness-dependent demand under carbon emissions constraints. We propose two deteriorating inventory models with carbon emissions tax and the capand-trade mechanism, in which the demand is freshness dependent, carbon emissions come from inventory holding, shipping, and item deteriorating, and the objective is to maximize the profit per unit time. We characterize the existence and uniqueness of the solutions for the models. We analyse the impacts of carbon emissions tax, carbon emissions quota, and carbon price on inventory decisions, carbon emissions, and profit. We conduct simulation to generate managerial insights from our analytical results.

ETCS Level 2 (European Train Control System Level 2, ETCS-2) has drawn particularly attention from researchers and industries. A new CPN model-based formal approach for test cases and sequences generation is proposed in this paper to increase the test automation degree of the ETCS-2 system and subsystems.In this paper, a set of modelling rules is presented firstly to make the Coloured Petri Net (CPN) model more suitable for test generation. Then, an automated test approach is described in detail, which includes an automatic test case generating algorithm and a type of automatic test sequence searching algorithm. The generated set of test cases satisfies specified coverage. The test sequence searching algorithm guarantees the results satisfying the minimum number of test sequences covering all test cases. The output of this approach is a set of well-formed XML (Extensible Markup Language) file to increase the automation degree of the test executing process. Finally, a partial model of ETCS-2 On-Board subsystem is built and analysed using the CPN Tools as a case study. The model-based formal approach is implemented on this model and the test cases and test sequences are all generated in a form of XML. The conclusion show that the CPN-model based testing approach can be used to improve the automation of the testing procedure and the generated test cases can meet the relative requirement.

This paper addresses the effect of probabilistic selling on inventory decisions and the expected profit through demand reshaping and demand substitution. By considering a scenario with two higher-priced specific products and one lower-priced probabilistic product, we construct a new newsboy-type inventory model with demand reshaping and substitution. A simulation study is implemented to explore extensively the effects of demand uncertainty, demand correlation, price sensitivity and price discount on the inventory decisions and profitability of probabilistic selling. Finally, we provide insightful managerial implications of the nature of inventory management mechanism of probabilistic selling.

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