Transportation industries are incessantly trying to stay in business by bringing their prices down. But Higher transportation cost leaves companies with less profit margins. The idea proposed in journal is to collaborate and plan their... more
Transportation industries are incessantly trying to stay in business by bringing their prices down. But Higher transportation cost leaves companies with less profit margins. The idea proposed in journal is to collaborate and plan their logistic network jointly to reduce cost of transportation and negative impact of bull-whip effect. The focus is given only on a road transportation and neglected ship or air transportation. Centralized and decentralized setting of developing a transportation network had been discussed. Out of the articles published till now, 60% of them published in last three years only. So Collaborative vehicle planning can be considered as a potential area of research and growing field in vehicle routing domain. The given survey tried to analyse result by study every survey published previously on collaborative routing network by chiefly focusing on centralized collaborative planning. Definitions and Classifications In a non-collaborative setting each firm individually tries to increase their profit depending on demand and load capacity of vehicle. Whereas, in collaborative setting each firm tries to increase their profit by amalgamating their demand and vehicle load capacity. Decentralized setting generally divided according to hierarchical ordering from powerful to base level and followed cycle of anticipation, instruction and reaction. VRP (vehicle routing problem) and ARP (arc routing problem) use to optimize network to reach every sets of customers. IRP (inventory routing problem) combine knowledge of VRP to manage inventory. While LCP (Lane covering problem), MCFP (Minimum cost flow problem) and AP (Assignment problem) can be used to optimize cost of transportation. Model also discusses the possibility of having time window, pickup and delivery location. Corporative Game theory is often being used for profit sharing in collaborative transportation with more than 40 other available option. Collaborative planning methods Collaborative planning generally made by centralized authority having full information for planning which can optimize the cost of transportation. Collaborative planning in non-cooperative setting can improve profit around 20-30% confirmed by applying on real-world problem. Horizontal collaborations not only follow economical but also ecological goals like reduced road congestion, noise pollution, and emissions of harmful substances. Vehicle routing problem with time window with carbon footprint as a constraint can reduce carbon emission by 60%. In several cases where distributors don't want to share their consumer information used linear programming method for a formulation and solved through branch and cut algorithms. The underlying problem is also known multi-depot ARP. The time-dependent centralized multiple carrier collaboration problem assumes a setting where carriers either provide or consume collaborative capacity. Many other methods have been discussed to integrate the delivery and reduce the cost of transportation. Decentralized planning with & without Actions If full information is not available to the user, then Decentralized approach is being needed. In this setting its generally divides in three parts such as partner selection, request selection and request exchange. These three phases subsequently elaborated by several methods with general focus of deciding on a request exchange method by choosing an appropriate partner at first.it can also be done by auction-based platform where collaborators submit their request to the common pool. This auction platform performs as the trading mechanism where collaborators share their information according to their preference. This process subsequently followed by allocating carriers to collaborator according to their bids and deciding upon profit sharing method. Conclusion Collaborative vehicle routing problem is active research area. And it can be proven significant in upcoming era. Because it can reduce cost and emission of carbon also leading to more profit margin which can enables higher business operations flexibility. However, more significant results can be obtained by structural development of methods to reduce performance gaps between Centralized and Decentralized planning approaches.
