Layer: An Alternative Approach To Solve Large Capacitated Vehicle Routing Problem with Time Window Using AI and Exact Method

To the best of my knowledge, this problem has never been addressed by any researcher. This paper studies the effect of K-means, the Gaussian Mixture Model (GMM), and the integrated use of autoencoder and K-means on the computational time, MIP gap, feasible route, subtour, and the optimum use of vehicles. Miller-Tucker-Zemlin (MTZ) subtour elimination constraint is considered in this regard. This paper also gives the concept of a “layer”, which could be effective to solve a large vehicle routing problem with a time window (VRPTW) quickly

Developing refrigerated and general carriers’ collaboration model for perishable product

In this paper, we study a novel pickup and delivery problem called carrier collaboration (CC). This problem includes a set of heterogenous (refrigerated and general type) vehicles with specific capacities for serving perishable products to several pickup and delivery nodes. Each carrier can have reserved and selective requests which can be delivered before the products are corrupted. The fleet of vehicles must serve reserved requests, but the selective requests can be served or not. Products are corrupted at a constant rate and a rate of corrosion in general type vehicles is greater than referigrated type veicles and the cost of using general one is less than referegireted. For the mentioned features, we develop a nonlinear mathematical model. The purpose is to find routes to maximize profits and reduce costs while at the same time, enhance customer satisfaction which is dependent on the freshness of delivered products. A Gnetic Algorithm (GA) is proposed to solve this problem due to its NP-hard nature. In this study, Variable Neighborhood Search (VNS) method is developed for improving the quality of initial solutions. Several instances are generated at different scales to evaluate the algorithm performance by comparing the results of an exact optimal solution wih that of the proposed algorithm. The obtained results demonstrate the efficiency of the proposed algorithm in providing reasonable solutions within an acceptable computational time

Multi-Objective Optimization of Green Transportation Operations in Supply Chain Management

Supply chain is the integration of manufacturing process where raw materials are converted into final products, then delivered to customers. Supply chains consists of two basic integrated process that interact together: (1) production and inventory and (2) distribution and logistics. Maximizing competitiveness and profitability are of the main goals of a supply chain. Accounting only for economic impacts as variable and fixed costs does not serve the main goal of the supply chain. Therefore, considering customer satisfaction measures in distribution models is essential in supply chain management. Models that addressed the three objectives simultaneously handled one of the objectives as a constraint with a certain threshold in the problem, while others used weighted utility functions to address the problem objective in deterministic environment. This thesis focuses on the multi-objective Vehicle Routing Problem (VRP) in green environment. The proposed Green VRP (GVRP) deals with three different objectives simultaneously that considers economic, environmental, and social aspects. A new hybrid search algorithm to solve the capacitated VRP is presented and validated in Chapter 2. The developed algorithm combines the evolutionary genetic search with a new local search heuristic that considers both locations and demand quantities of the nodes to be visited in routing decisions, not just the distances travelled. The algorithm is then used to solve the multi-objective GVRP in Chapter 3. The objectives of the developed GVRP model are minimizing the total transportation operations cost, minimizing the fuel consumption, and maximizing customer satisfaction. Moreover, a new overlap index is developed to measure the amount of overlap between customers’ time windows that provides an indication of how tight/constrained the problem is. The model is then adapted to consider the uncertainty in travel times, service times, and unpredictable demands of customers in Chapter 4. Pareto fronts were obtained and trade-offs between the three objectives are presented in both deterministic and stochastic forms. Furthermore, analysis of the effects of changing vehicle capacity and customer time windows relaxation are presented

The mediating influence of loyalty programmes on repeat purchase behaviour in the retail sector

A research report submitted to the Faculty of Commerce, Law and Management, University of the Witwatersrand, in partial fulfilment of the requirements for the degree of Master of Management in Strategic Marketing January 2016While there has been significant research on loyalty programmes in the last two decades, little has been done on the youth market in South Africa. Using the social exchange and relationship marketing theories, the study examines the mediating influence of customer satisfaction, trust and commitment in the relationship between loyalty programmes and repeat purchase behaviour of South African youth. The methodology involved a self-administrated questionnaire adapted from previous studies. Data was collected from 263 South African youth who are loyalty programme members. The study tested six hypotheses using Structural Equation Modeling. The software used was SPSS 22 for descriptive statistics and IBM Amos 22. The findings indicate that all six hypotheses are supported. They also suggest the significance of customer satisfaction as a strong mediator of loyalty programmes and repeat purchase behaviour. Moreover, the study reveals that the mediating influence of customer commitment on loyalty programmes and repeat purchase behaviour is the weakest. The findings reveal that by building customer satisfaction and customer trust amongst the youth, marketers can positively impact on the success of loyalty programmes and repeat purchase behaviour. This study contributes to the literature on loyalty programmes amongst youth within a developing market context. It can assist marketers in developing sound loyalty programmes aimed at the youth market in South Africa. Limitations and future research directions are discussed.MT201

Multi-objective optimisation of dynamic short-term credit portfolio selection :the adoption of third party logistics credit for financing working capital contrained small and medium sized enterprises in supply chains

PhD ThesisMany companies, especially small and medium sized enterprises, are faced with liquidity problems. The shortage of working capital in their businesses has prevented supply chains from achieving effectiveness and efficiency in management. Although they can access short-term loans from banks and suppliers, the willingness of these credit lenders to lend short-term capital is often restricted by the fact that they cannot monitor whether or how their customers will use the loans according to the agreements. In many cases, this fact makes it difficult for capitalconstrained companies to obtain sufficient working capital from existing funding sources. A business practice called Integrated Logistics and Financial Service has been developed, which can improve banks’ monitoring of how their loans will eventually be used via the alliance of third party logistics companies and banks. The emergence of credit offered by third party logistics companies (termed as 3PLC) provides more choices for working capital constrained companies. Following on traditional bank overdrafts and trade credit, the new 3PLC became the third type of credit available to short-term working capital constrained companies. A new issue arising from this situation is how a working capital constrained company can determine a credit portfolio from multiple working capital sources. Current studies of credit portfolio management are still silent in considering 3PLC. Moreover, limited studies have integrated credit portfolio management into material flow management in supply chains. In light of the aforementioned discussions, this thesis aims to optimise dynamic credit portfolio management in supply chains to achieve the different business objectives of working capital constrained companies. To achieve the above aims, this thesis firstly applies an analytic hierarchy process and linear programming model to optimise a single objective. It applies the analytic hierarchy process to evaluate the concerns of working capital-constrained companies in selecting credit. These concerns are identified through a thorough literature review focusing on the considerations of small and medium sized enterprises’ in borrowing short-term credit. The analytic hierarchy process has been applied to determine the priority of the identified concerns and the preferences of borrowers for bank overdrafts, trade credit and 3PLC. A linear programming model has been developed based on the results obtained from the analytic hierarchy process model. It determines the maximum borrowing amount for a given period from multiple credit sources. To reflect the complexity of working capital constrained companies borrowing credit, thisthesis has extended the model from single objective optimisation to multiple objectives optimisation. Consequently, a goal-programming model has been developed. This model provides the solution of optimizing two business objectives including overall cost and backorder penalty cost minimization. Numerical examples have been conducted to test and analyse all the mathematical models. This thesis contributes the following aspects: 1) the new 3PLC together with bank overdraft and trade credit have been considered into credit portfolio management; 2) borrower’s concerns and credit preferences relating to the three types of credit have been identified and evaluated; 3) mathematical models have been developed for credit portfolio selection over multiple periods