P.N. Ram Kumar

Multi-period reverse logistics network design with emission cost

Purpose The purpose of this paper is to develop a mathematical model for the network design of a reverse supply chain in a multi-product, multi-period environment. The emission cost due to transportation activities is incorporated into the model to reduce the total cost of emission and study the significance of inclusion of emission cost on the network design decisions. Design/methodology/approach Mixed integer linear programming formulation is used to model the network. The developed model is solved and analysed using the commercial solver LINGO. Findings The mathematical model provides a unified design of the network for the entire planning horizon comprising of different periods. A reduction in the total cost of emission is achieved. The analysis of the problem environment shows that the network design decisions significantly vary with the consideration of emission cost. Research limitations/implications A single mode of transportation is considered in this study. Also, a single type of vehicle is considered for the transportation purpose. Practical implications The developed model can aid the decision makers in making better decisions while reducing the total emission cost. The quantification of the emission cost due to transportation activities is presented in an Indian context and can be used for future studies. Originality/value An all-encompassing approach for the design of reverse logistics networks with explicit consideration of product structure and emission cost.

Convoy Movement Problem – An Optimization Perspective

This chapter addresses the convoy movement problem (CMP) in military logistics. CMP involves routing and scheduling military convoys within the strategic constraints. The chapter begins with an introduction to the domain of military logistics. It is followed by formal specification of CMP, computational complexity and classification of the problem. Section 2 highlights the state of art as is evident from the literature and the gaps that require further exploration. An integer programming model is then presented in section 3 and section 4 demonstrates its adaptability to different practical scenarios. In section 5, methods to generate lower and upper bounds are discussed in brief. Section 6 summarizes the results obtained, followed by conclusions and scope for further work in the last section.

Integer programming formulation for convoy movement problem

This paper reports a study of the strategic network problem of routing military convoys between specific origin and destination pairs. Known as the Convoy Movement Problem (CMP), this problem is formulated as an integer linear program. The proposed mathematical model is evaluated on the basis of average number of iterations and average CPU times. LP-based lower bounds and heuristic based upper bounds were generated and used for evaluating the proposed model, particularly for large problem instances for which optimal solutions could not be obtained.

Bi-criteria Convoy Movement Problem

The problem of routing and scheduling military convoys adhering to certain constraints is known as the convoy movement problem. This work addresses a bi-criteria model for the peacetime version of the convoy movement problem with minimizing total travel time and travel span as objectives. Two approaches, one based on goal programming and the other based on simulated annealing, are proposed. Encouraging results have been obtained.

Impact of aggregating supplies from single supplier to a cluster of producers: opportunities for 3PL service providers

A supply chain is a network of different entities, such as suppliers, manufacturers, distributors and retailers. Each supply chain member adopts a myopic policy for replenishment and production-related decisions to maximise its revenue or minimise its costs. It results in local optimisation and hence reduced overall supply chain performance. This work investigates the benefits of coordinating the production and distribution decisions in a scenario comprising single supplier and a cluster of multiple buyers. The problem is modelled as a mixed-integer linear programme. Factor analysis is conducted to identify dominant factors that favour the benefits of coordination. A heuristic procedure is developed to solve large problem instances in very less computational time. Encouraging results are obtained.

On solving the Capacitated Hub Routing Problem

We introduce the combinatorial optimisation problem of routing freight on a capacitated hub-and-spoke network known as the Capacitated Hub Routing Problem (CHRP). The hubs are limited in capacity for channelling flows between the nodes served by the system. A Mixed Integer Programming (MIP) model is proposed for the problem. With extensive computational results and design of experiments, it is proved that the hub capacity is the dominant factor that affects the total cost of transportation as well as the computational time required to solve a problem instance to optimality. A simple but effective heuristic is proposed for problem instances with unknown optimal solutions. The results obtained are encouraging.

Simulated annealing-based algorithm for the capacitated hub routing problem

Routing traffic across a capacitated hub-and-spoke network is very common in freight transportation and telecommunications. Most of the hub-and-spoke network models available in the literature assume a fully inter-connected hub network and allow traffic to pass through a maximum of two hubs. In the absence of a fully inter-connected hub network, the traffic may have to be routed through more than two hubs. In this paper, we develop a mathematical model and a simulated annealing (SA)-based solution methodology for routing freight through not more than three hubs in a given capacitated network. We generate test problem instances to evaluate the efficacy of the mathematical model and the meta-heuristic procedure. The effect of each network parameter on the performance of the SA procedure is analysed thoroughly with extensive computational experiments and relevant statistical tests. The results show that near-optimal solutions for large problem instances can be derived in little computational time.

On the usage of Lagrangean Relaxation for the convoy movement problem

The problem of routing military convoys between specific origin and destination pairs is known as convoy movement problem (CMP). In this study, we consider an existing mathematical model of CMP and propose a lower bounding procedure based on Lagrangean Relaxation. The robustness of the proposed procedure is evaluated on a variety of test problem instances. Encouraging results are obtained.

Heuristics for Convoy Movement Problem

Abstract Convoy movement problem involves routing and scheduling military convoys across a limited route network, adhering to certain strategic constraints. This article suggests using heuristics for solving the dynamic version of the problem where the network changes over time. The performance of heuristics evaluated against lower bounds, when applied to a number of hypothetical data-sets, is found to be encouraging.