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The purpose of this paper is to study the problem of a routing problem with uncertain try-on service time (VRPUS) for apparel distribution, and to devise solution…
The purpose of this paper is to study the problem of a routing problem with uncertain try-on service time (VRPUS) for apparel distribution, and to devise solution strategies coping with the uncertainty by an evolutionary algorithm. VRPUS belongs to the category of practical routing models integrated with uncertain service times. However, in the background of apparel distribution, it has distinct features. The try-on service will improve the customer satisfaction by providing experiences to customers; the return cost is saved; the customer loyalty is improved for experiencing face-to-face try-on services. However, the uncertainty of try-on service time makes the apparel distribution process uncertain and incurs additional risk management cost, such that the logistics companies should optimally make decisions on the choice of the service and the service processes.
This paper devised a mixed-integer programming (MIP) model for the base vehicle routing problem (VRP) and then it is extended to support the solution strategies for uncertain try-on times. A try-on time estimation parameter and a time reservation parameter are used to cope with the uncertain try-on time, and the try-on rejection strategy is applied when the uncertain try-on time is realized at customer and no surplus time can be used for try-on service besides distributing to remainder customers. Due to the computational complexity of VRPUS, an evolutionary algorithm is designed for solving it. These parameters and strategy options are designed for the operational decisions by logistics companies. Finally, a decision support system (DSS) is designed.
Five experimental scenarios are performed to reveal the impacts of parameters and solution strategies coping with uncertain try-on time on the distribution cost, return cost, and the try-on service failure. The tuning methods are designed to assist the decisions by logistics companies.
A new routing problem is addressed for apparel distribution in fashion industry especially in the context of booming apparel e-commerce, which is a VRP with uncertain try-on service time for apparel distribution; three strategies are developed to cope with the try-on time uncertainty. The proposed method is also a theoretical base for designing a practical DSS for logistics companies to provide try-on service to customers.
The purpose of this paper is to study the problem of clothing uniform assignment (CUA) and propose an immune co‐evolutionary algorithm to search optimal assignments of…
The purpose of this paper is to study the problem of clothing uniform assignment (CUA) and propose an immune co‐evolutionary algorithm to search optimal assignments of uniform garments to employees.
Multi‐size fitting measures are proposed based on multi‐attribute decision making. An immune co‐evolutionary algorithm incorporating immune inspired mechanisms is proposed to search optimal assignments.
The experimental results show promising performance. The model and the algorithm are aiming at a valuable problem and can be incorporated into the information systems for large‐scale industrial companies.
Uniform assignment problem is modeled with garment size fitting constraints. Multi‐size fitting measures are proposed based on multi‐attribute decision making and an immune co‐evolutionary algorithm is proposed to search optimal assignments.