G.T.S. Ho

Survey of Green Vehicle Routing Problem: Past and future trends

Green Logistics has emerged as the new agenda item in supply chain management. The traditional objective of distribution management has been upgraded to minimizing system-wide costs related to economic and environmental issues. Reflecting the environmental sensitivity of vehicle routing problems (VRP), an extensive literature review of Green Vehicle Routing Problems (GVRP) is presented. We provide a classification of GVRP that categorizes GVRP into Green-VRP, Pollution Routing Problem, VRP in Reverse Logistics, and suggest research gaps between its state and richer models describing the complexity in real-world cases. The purpose is to review the most up-to-date state-of-the-art of GVRP, discuss how the traditional VRP variants can interact with GVRP and offer an insight into the next wave of research into GVRP. It is hoped that OR/MS researchers together with logistics practitioners can be inspired and cooperate to contribute to a sustainable industry.

A decision support system for optimizing dynamic courier routing operations

In this paper, we propose a prototype of a decision support system (DSS) that integrates a hybrid neighborhood search algorithm to solve the offline and online routing problems arising in courier service. In the dynamic operational environment of courier service, new customer orders and order cancellations continually arrive over time and thus disrupt the optimal routing schedule that was originally designed. This calls for the real-time re-optimization of routes. As service level is sensitive to whether allowable service time intervals are wide or narrow, it is valuable to study how adjustable and flexible time windows influence the courier service efficiency in a dynamic environment. To capture these dynamic features, a dynamic vehicle routing problem (DVRP) that simultaneously considers new customer orders and order cancellations is investigated in this study. Meanwhile, fuzzy time windows are formulated in the DVRP model to quantify the service level and explore the service efficiency. To tackle the new problem, we propose a competitive hybrid neighborhood search heuristic for (re)optimizing the offline and online routes. Numerical computational experiments and the comparison with results from Lingo show that our algorithm is capable of re-optimizing dynamic problems effectively and accurately in a very short time. The proposed model and algorithms are able to enhance courier service level without further expense of a longer traveling distance or a larger number of couriers.

Factors influencing implementation of reverse logistics : a survey among Hong Kong businesses

Purpose – The purpose of the paper is to examine the major factors that may influence industries to implement reverse logistics. Thus, the practice of reverse logistics can be promoted by suggestions provided for businesses to eliminate the identified barriers.Design/methodology/approach – In this paper, a questionnaire is developed and the survey is conducted among Hong Kong businesses to collect data on the perception of companies on reverse logistics implementation. Nine hypotheses are set to investigate its influence on company background information, recognition, and perception on reverse logistics, as well as the internal and external factors. Statistical analysis is carried out to test the data collected. Managerial implications are presented to encourage industries to implement reverse logistics.Findings – The result of the statistical analysis shows that internal and external factors significantly influence reverse logistics. Financial and human resources play an important role in companies impl...

Determination of the success factors in supply chain networks: a Hong Kong‐based manufacturer's perspective

Purpose – The purpose of the paper is to investigate the factors that affect the decision‐making process of Hong Kong‐based manufacturers when they select a third‐party logistics (3PL) service provider and how 3PL service providers manage to retain customer loyalty in times of financial turbulence.Design/methodology/approach – The paper presents a survey‐based study targeting Hong Kong‐based manufacturers currently using 3PL companies. It investigates the relationship between the reasons for using 3PL services and the requirements for selecting a provider, and examines the relationship between customer satisfaction and loyalty. In addition, the relationships among various dimensions – in small to medium‐sized enterprises (SMEs), large enterprises and companies – of contracts of various lengths are investigated.Findings – In general, the reasons for using 3PL services and the requirements for selecting 3PL service providers are positive‐related. The dimension of “reputation” of satisfaction influences “pri...

Customer relationship mining system for effective strategies formulation

Purpose – The purpose of this paper is to propose a customer relationship mining system (CRMS) to analyze the data collected from franchisees and formulates a marketing strategy based on customer demand and behavior. Design/methodology/approach – The system makes use of cloud technology to collect and manage data among the franchisees. An integrated approach of association rule mining and the neural network technique is adopted to investigate customer behavioral patterns and to forecast sales demand, respectively. Findings – The significance and contribution of this paper are demonstrated by adopting the CRMS in the education industry in Hong Kong. The findings led to the identification of student learning intentions such as course preferences, and the forecasting of enrolment demand in terms of demand forecast. It is believed that better resources allocation can be achieved and an increase in customer satisfaction is foreseeable. Research limitations/implications – The proposed CRMS could be applied to v...

An online niche-market tour identification system for the travel and tourism industry

– The purpose of this paper is to present a novel approach for niche-market tour identification, with the objective to obtain a better segmentation of target tourists and support the design of tourism products. A proposed system, namely the Niche Tourism Identification System (NTIS) was implemented based on the proposed scheme and its functionality was showcased in a case study undertaken with a local travel agency. , – The proposed system implements automated customer market segmentation, based on similar characteristics that can be collected from potential customers. After that, special-interest tourism-based market strategies and products can be designed for the potential customers. The market segmentation is conducted using a GA-based k-means clustering engine (GACE), while the parameter setting is controlled by the travel agents. , – The proposed NTIS was deployed in a real-world case study which helps a local travel agency to determine the various types of niche tourism found in the existing market in Hong Kong. Its output was reviewed by experience tour planners. It was found that with the niche characteristics can be successfully revealed by summarizing the possible factors within the potential clusters in the existing database. The system performed consistently compared to human planners. , – To the best of the authors’ knowledge, although some alternative methods for segmenting travel markets have been proposed, few have provided any effective approaches for identifying existing niche markets to support online inquiry. Also, GACE has been proposed to compensate for the limitations that challenge k-means clustering in binding to a local optimum and for its weakness in dealing with multi-dimensional space.

An online decision support system for inventory management

Due to increasing popularity of using the Internet to perform businesses, enterprises are now facing tremendous pressure from competitors all over the world. In order to survive in the competitive marketplace, companies must be able to deliver their products at the right time, to the right place, and with the right price. Research studies have shown that decision support system can help enhancing the competitiveness of an enterprise. In general, decision support system technologies and applications are widely used by enterprises to support individual decision-makers, workgroups and virtual partners. This paper proposes a decision support system, which possesses certain intelligent features to support the inventory management. To validate the feasibility of the proposed system, a prototype system has been developed and installed in a local jewellery factory to support the inventory control, thereby helping the factory to maintain an optimal inventory level to match the market demand.

A B2C e-commerce intelligent system for re-engineering the e-order fulfilment process

The e-commerce internal order processing flow is streamlined and re-designed.A GA-rule-based system for efficient e-commerce order fulfilment is proposed.An optimal order processing plan is generated by genetic algorithm technique.A system implementation shows a significant order processing time reduction. In todays world of digitization, the rise of the e-commerce business around the globe has brought a tremendous change not only in our purchasing habits, but also to the entire retail and logistics industry. Given the irregular e-commerce order arrival patterns, limited time for order processing in e-fulfilment centres, and the guaranteed delivery schedules offered by e-retailers, such as same-day or next-day delivery upon placing an order, logistics service providers (LSPs) must be extremely efficient in handling outsourced e-commerce logistics orders. Without re-engineering the order fulfilment processes, the LSPs are found to have difficulties in executing the order fulfilment process due to the tight handling requirements. This, in turn, delays the subsequent processes in the supply chain, such as last-mile delivery operations, consequently affecting customer satisfaction towards both the retailer and the LSP. In view of the need to improve the efficiency in handling e-commerce orders, this study aims at re-engineering the fulfilment process of e-commerce orders in distribution centres. The concept of warehouse postponement is embedded into a new cloud-based e-order fulfilment pre-processing system (CEPS), by incorporating the genetic algorithm (GA) approach for e-commerce order grouping decision support and a rule-based inference engine for generating operating guidelines and suggesting the use of appropriate handling equipment. Through a case study conducted in a logistics company, the CEPS provides order handling solutions for processing e-commerce logistics orders very efficiently, with a significant reduction in order processing time and traveling distance. In turn, improved operating efficiency in e-commerce order handling allows LSPs to better align strategically with online retailers, who provide customers with aggressive, guaranteed delivery dates.

An intelligent fuzzy-based storage assignment system for packaged food warehousing

In the packaged food industry, fast cargo receiving, reliable storage and accurate order picking in warehouses within short period of time are critical for achieving customer satisfaction. Food easily deteriorates when unloaded packaged food is exposed in an open area, waiting for inbound and packing operations, according to customer orders. In addition, the risk of damaging the packaging of food is higher when the food is frequently transported by forklift trucks during order picking. This highlights the need to provide decision support in warehouse zoning and storage assignment for preventing the above risks occurring. This paper proposes a tri-modular intelligent fuzzy-based storage assignment system, integrating fuzzy logic and association rules mining techniques, to reduce the order-picking and cargo exposure time, as well as the transport frequency and distance. The fuzzy zoning module is used to allocate different types of packaged food to various warehouse zones based on their particular characteristics. The location assignment module reveals hidden relationships in the sales of products, in turns suggesting which products should be placed together in the same zone. A case study is carried out to examine the intelligent system.

Assess the effects of different operations policies on warehousing reliability

In this study, an assessment model for analysing the reliability of a warehouse system, focusing on resource capability, under given combinations of storage, routing, batching and zoning process policies, is proposed. A reliability assessment model is developed in order to evaluate the effect of different combinations of operations policies on warehouse reliability. To better reflect the real order pick up operations at the warehouse, a simulation model based on the operation scenarios of a Hong Kong logistics service company is developed. The simulation results are used for supporting the evaluation of warehouse reliability through using the proposed reliability assessment model. The most important finding indicates that order batching together with zoning policies yields greater warehouse reliability particularly when the daily order volume is large. In addition, another important research finding shows that warehouse performance is not constant and can drop when certain combinations of operations policies are adopted. The degrading rate of the resource (forklift) when used according to a given combination of polices is also defined by the proposed assessment method. Hence, the result helps logistics service providers enhance resource durability through modifying operations policies and by implementing proper preventive maintenance policies within a dynamic operations environment.