International Journal of Supply and Operations Management
Volume:4 Issue: 4, Autumn 2017

Nowadays, Companies need to collect and to deliver goods from and to their depots and their customers. Reusable containers are considered as a greener choice and a cost saving strategy. This paper addresses a dynamic management of reusable containers (e.g gases bottles, wood pallets, maritime containers, etc.) in a Closed-loop supply chain. The aim of the study is to find an optimal lot sizing and assignment strategy that minimizes the cost of reusable containers management under environmental constraint. In this contribution, a new integer-linear-programming model and two hybrid approaches based on the genetic algorithm are proposed to solve the problem. The second hybrid method is enhanced with a local search based on the VNS (variable neighborhood search). The numerical results show the performance of the two hybrid approaches in terms of solution quality and response time.

Natural disasters, accidents, and crises, that cause widespread destruction and inflict heavy casualties, accentuate the importance of a careful planning to deal with the aftermath and mitigate their impacts responsively. Thus, the logistics of disaster relief is one of the main activities in disaster management. In this paper, the response phase of the disaster management cycle is considered and a multi-objective model for location and routing of vehicles is presented. Uncertainties in transfer time, demands of regional warehouses in the damaged areas and inventories at supply centers in different periods are taken into account. Three objectives are considered in this model. Two objectives consist of minimizing total time required to reach the damaged areas and maximizing satisfaction of the damaged areas. The third objective, which is of secondary importance, attempts to minimize total costs, including startup costs, transfer costs, and shortage costs. In order to convert the proposed multi-objective formulation to a single objective one, Global Criterion approach is applied. Afterwards, the obtained single objective model is solved using an efficient genetic algorithm and simulated annealing. Finally, a case study in Southern Khorasan is conducted and the applicability of the proposed model is examined.

Selection problems which contain many criteria are important and complex problems and different approaches have been proposed to fulfill this job. The Analytic Hierarchy Process (AHP) can be very useful in reaching a likely result which can satisfy the subjective opinion of a decision maker. On the other hand, the Data Envelopment Analysis (DEA) has been a popular method for measuring relative efficiency of decision making units (DMUs) and ranking them objectively with the quantitative data. In this paper, a Three-step procedure based on both DEA and AHP is formulated and applied to a case study. The procedure maintains the philosophy inherent in DEA by allowing each DMU to generate its own vector of weights. These vectors of weights are used to construct a group of pairwise comparison matrices which are perfectly consistent. Then, we utilize group AHP method to produce the best common weights which are compatible with the DMUs judgments. Using the proposed approach can give precise evaluation, combining the subjective opinion with the objective data of the relevant factors. The applicability of the proposed integrated model is illustrated using a real data set of a case study, which consists of 19 facility layout alternatives

We present a simple and effective metaheuristic algorithm for the Split Delivery Vehicle Routing Problem (SDVRP). The SDVRP is a relaxation of the classical Vehicle Routing Problem in which a customer demand may be serviced by more than one vehicle. The objective is to find a set of least cost trips for a fleet of identical vehicles to service geographically scattered customers with or without splitting. The proposed method is a hybridization between a Variable Neighborhood Search (VNS), an Evolutionary Local Search (ELS) and a Variable Neighborhood Descent (VND). It combines the multi-start approach of VNS and ELS and the VND intensification and diversification strategies. This new method is tested on three sets of instances from literature containing a total of 77 benchmark problems. The obtained results show that the algorithm outperforms all previously published metaheuristics. 62 instances out of 77 are improved.

The main focus of this paper is presenting a conceptual structure for Maritime Inventory-Routing Problem. We have looked at the matter from the supply chain angel and summed up the main comprising elements and major hypotheses in the framework of a conceptual model. We have surveyed in details the related literature in a classified manner, separated various issues and eventually in accordance with the identified vacuums, presented the grounds for development in the same particular framework. What we deal with in this article is in fact the zero level of the for Maritime Inventory-Routing Problem while for focusing on higher levels it is possible to deal with greater details by providing arithmetic models on more comprehensive navigation of naval goods in a more compact and sold manner. According to this review most of researches are deterministic at the tactical level, on the basis of discreet time and in the arc-flow framework, generally solved by exact or heuristic methods.

In this study, supplier and carrier selection and order allocation are considered to go for joint decision-making. To this end, some criteria including cost, quality, delivery, resilience, social responsibility and supplier profile are determined to select the weight of each supplier by AHP. Then, multi objective mathematical model is developed to select the appropriate supplier and carrier and allocate orders of multi product with different discount levels in each period by suitable carriers to each supplier. The objective functions in this study are minimizing cost, delivery and the number of defective items, and maximizing the efficiency of suppliers. Moreover, some constraints such as inventory capacity, shortage capacity, number of vehicle and breakdowns of them and etc. are applied in this novel mathematical model. Finally, this model is solved by augmented ɛ-constraint method for determining pareto-optimal solution. This study can help decision makers to solve problem by integrating AHP and multi-objective model.

Supply Chain Management is one of the key areas in the field of operations management to improve the performance of the firm. This study proposes a model with four constructs named as (Supply Chain Management Strategy, Supply Chain Management Commitment, Supply Chain Management Integration and Firm Performance) into it. The proposed model is unique in the way of providing four constructs simultaneously with its possible inter-relationships. Total five Inter-relationships are offered in the form of propositions for the said model. Previous studies in the field of Supply Chain Management are failed in offering all the four constructs and its relationship simultaneously. This model lay down new foundation in the field of Supply Chain Management which helps practitioner and academician to do further research on it.