Saurabh Pratap

Integrated scheduling of rake and stockyard management with ship berthing: a block based evolutionary algorithm

An integrated problem of optimising the operations at a commercial bulk material port terminal is studied in this paper. We simultaneously optimise the stockyard operations and rake schedule for outbound cargo, in conjunction with the arriving vessels and the status of the stockyards at the port. A mixed integer linear programming model for the problem is developed while incorporating the inherent complexities of the integrated model. To solve the real-life instances, two heuristic methods are proposed specifically for the considered problem. Firstly, genetic algorithm coupled with a greedy heuristic and later, block-based evolutionary algorithm (BBEA) is employed. After applying both techniques, we obtain the optimised schedule for loading of rakes and allotment of stockyard space for vessels as well as rakes at the terminal. Finally, we test the results of both models in three traffic scenarios between themselves and with real-life data from a port situated along the Eastern coast of India. The study resulted in significant reduction of turnaround time for rakes at the port terminal, which in turn lead to monetary savings. The model also automates the day to day operational decision-making at the port.

Rule based optimization for a bulk handling port operations

In this paper a study on the operations of a bulk material port is carried out to develop a decision support model, which deals with the dynamics of port and aids in better decision making at different scenarios. Here, we describe various decisions taken by port authorities pertaining to the import of coal at the terminal. We optimize these decisions with the aim of minimizing the unloading time of ships at the port, congestion in the stockyard, and loading time of the rakes. A practice-oriented decision support model is proposed to assist port planners in making these decisions. Various operational rules are embedded within the model, for carrying out the modelling of various port operations. The utility of the developed model is demonstrated using a case study which helps in achieving efficient utilization of berths, stockyard and rake loading stations.

Optimal collaborative transportation service trading in B2B e-commerce logistics

This paper investigates a less-than-truckload carrier collaboration decision-making problem in the e-commerce logistics network. E-commerce less-than-truckload carrier collaboration problem considers multiple logistics service providers (LSPs) forming a collaborative alliance in an e-commerce logistics network. They share their transportation requests and vehicle capabilities to maximise the total profit of the entire alliance, improve their vehicle utilisation and cope with fluctuations in demand. An e-commerce logistics trading system with collaborative decisions is designed. A collaborative transportation planning model is introduced to maximise the total profit without reducing the individual profit of the carriers with information sharing. A stochastic plant-pollinator algorithm is proposed for the problem and extensive computational experiments are conducted. The results show that the proposed plant-pollinated algorithm performs better than the genetic algorithm. Furthermore, the results illustrate that the higher degree of cooperation, the more benefits for carriers. Last but not least, since the increasing gasoline price leads to the decreasing margins for the small- and medium-sized LSPs. The results also show that it is critical for them to join in the alliance to survive in the competition.

An integrated decision support system for berth and ship unloader allocation in bulk material handling port

The decisions pertaining to berth allocation and ship unloader operations at bulk material import terminal are described.Our models integrate the major port operations and minimize the various delays.A practice-oriented decision support model is proposed.This model assists port planners in making informed decision.The utility of the developed model is demonstrated using an illustrative scenario. Berth allocation and material handling problems in ports are generally solved independently. This article provides a framework for aligning allocation decisions of berth and ship un-loader in an integrative manner. The ultimate goal of these decisions is to minimize the waiting time, operating time and ships priority deviation. As the sojourn time of a ship in port is costly, and given the scale and the complexity of the problem, a Decision Support System (DSS) is developed for the port authority. Two different approaches have been considered in this paper: (1) Solving the problem sequentially by decomposing the problem into two sub-problems- the berth allocation and the dynamic allocation of ship un-loaders in different berths (2) solving the problem by integrating berth allocation and dynamic allocation problem. Controlled Elitist Non-dominated Sorting Genetic Algorithm and Chemical Reaction Optimization are proposed in designing the DSS. Computational experiments are conducted on information provided from an Indian port. Results show that integrating berth and ship un-loader allocation achieves significant cost savings by considerably reducing the ship sojourn time in port.

An integrated Bayesian-Game theoretic approach for product portfolio planning of a multi-attributed product in a duopolistic market

The focus of this paper is to develop a Bayesian-Game theoretic framework for product portfolio planning problem thereby aiding the manufacturers operating across variety of product industries to offer the right product portfolio set. The problem is modelled for a duopolistic market and the product type considered is characterised by multiple product attributes having varying attribute levels. Initially, feasible product portfolio candidates are generated in terms of combinations of different product attributes and their attribute levels employing the attribute compatibility constraint. Different product portfolio sets thus generated function as different product offering strategies of the two manufacturers. Thereafter, employing the function-based cost-estimating framework and multi-linear regression methodology, manufacturing costs and product premiums, respectively, are estimated for different product portfolios. Utilising the Bayesian risk network, the purchase probabilities are estimated in high, medium and low-risk states for various product portfolios. The purchase probability is made a function of price and functionality. The purchase probabilities thus obtained acts as an input to the final pay-off calculation. Finally, employing these pay-off values, product offering scenarios are populated for the two manufacturers both in equilibrium and non-equilibrium state.

The robust quay crane allocation for a discrete bulk material handling port

This study investigates the quay crane allocation problem with respect to vessel assigned to a particular discrete berth at a bulk material handling port. In the proposed model,vessels at the anchorage are berthed on a First in, first out (FIFO) basis at the port, and then the quay cranes are assigned to the berth dynamically before berthing and during unloading of the vessel. To solve the model, we used the Block Based Genetic Algorithm (BBGA) and Genetic Algorithm (GA). Computational study is conducted using the real data provided by a port located on theEastern Coast of India.

Game theoretic analysis of horizontal carrier coordination with revenue sharing in E-commerce logistics

This paper proposes comparisons among two different competitive power structures with and without horizontal coordination. We conduct a game theoretic analysis on the situation where two logistics service providers compete in an e-commerce logistics market with respect to the order quantity and service level decision on a particular logistics service product. Under a consumer utility-based demand, we acquire the equilibrium order quantity decisions and optimal profits under the centralised setting and decentralised setting. An analytical model is established to examine the existence of the Nash equilibrium in the service game. We then prove that the logistics service demand depends on different competitive power structures with the establishment of Cournot game and Stackelberg game model. The analytical results and the equilibrium analysis of the e-commerce logistics system are investigated. After that, we compare the equilibrium results among the centralised system, Cournot game, and Stackelberg game. To empower the horizontal carrier coordination, we design a revenue sharing contract for the decentralised model. A numerical study illustrates the impact of parameters on the optimal decision variables. In this paper, we prove the effectiveness of horizontal carrier collaboration and explicate the reason for the lower marginal profit in logistics theoretically.