Peeyush Mehta

Permutation flow shop scheduling with earliness and tardiness penalties

We consider the permutation flow shop scheduling problem with earliness and tardiness penalties (E/T) and common due date for jobs. We show that the problem can be sub-divided into three cases: (i) the due date is such that all jobs are necessarily tardy; (ii) the due date is unrestricted; and (iii) the due date is between the two. Based on analytical results we provide partial characterisation of the optimal solution and develop a comprehensive approach for solving the problem over the entire range of due dates. Our approach, which draws upon the existing literature and results for the single machine problem, successfully exploits the properties of the optimal solution. Limited computational results indicate that the performance of the heuristic is reasonable and has the potential to significantly improve performance. This approach has been incorporated as part of the scheduling module of the production planning and scheduling system we developed for a medium-sized bulk drug manufacturer.

Optimal shelf-space stocking policy using stochastic dominance under supply-driven demand uncertainty

In this paper, we develop an optimal shelf-space stocking policy when demand, in addition to the exogenous uncertainty, is influenced by the amount of inventory displayed (supply) on the shelves. Our model exploits stochastic dominance condition; and, we assume that the distribution of realized demand with higher stocking level stochastically dominates the distribution of realized demand with lower stocking level. We show that the critical fractile with endogenous demand may not exceed the critical fractile of the classical newsvendor model. Our computational results validate the optimality of amount of units stocked on the retail shelves.

Integrating operations and marketing decisions using delayed differentiation of products and guaranteed delivery time under stochastic demand

In this research, we integrate the issues related to operations and marketing strategy of firms characterized by large product variety, short lead times, and demand variability in an assemble-to-order environment. The operations decisions are the inventory level of components and semi-finished goods, and configuration of semi-finished goods. The marketing decisions are the products price and a lead time guarantee which is uniform for all products. We develop an integrated mathematical model that captures trade-offs related to inventory of semi-finished goods, inventory of components, outsourcing costs, and customer demand based on guaranteed lead time and price.The mathematical model is a two-stage, stochastic, integer, and non-linear programming problem. In the first stage, prior to demand realization, the operation and marketing decisions are determined. In the second stage, inventory is allocated to meet the demand. The objective is to maximize the expected profit per-unit time. The computational results on the test problems provide managerial insights for firms faced with the conflicting needs of offering: (i) low prices, (ii) guaranteed and short lead time, and (iii) a large product variety by leveraging operations decisions.

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.

Structural mapping of public distribution system using multi-agent systems

Purpose – The purpose of this paper is to develop a framework for mapping the Indian Public Distribution System (PDS) using multi-agent system (MAS). The entire PDS supply chain from purchase to the distribution is mapped in detail by integrating stages of PDS supply chain. Design/methodology/approach – Literature related to PDS, food grain supply chain (FGSC) and MAS is reviewed and critically assessed. Based on this a framework is proposed which will help in improving functioning of PDS. Findings – The PDS has many shortcomings arising from its complex structure and practices which are used to implement it. The authors propose an MAS to model it in which each entity will be modelled as an agent. The authors propose two stages of supply chain. First stage models the processes from procurement to storage of food grain and second stage model the distribution process. Practical implications – This paper will be of interest to the policy makers and decision makers involved in the PDS by providing the shortfa...

An efficient local search for minimizing completion time variance in permutation flow shops

This paper illustrates that by exploiting the structure of hard combinatorial optimization problems, efficient local search schemes can be designed that guarantee performance in solution quality and computational time. A two-phase local search algorithm is developed and applied to the permutation flow shop scheduling problem, with the objective of minimizing the completion time variance. New and significant analytical insights necessary for effectively solving the permutation flow shop problem are also presented and used in this research. Computational results indicate that for test problems, the local search obtained optimal solutions for many instances, within few seconds of CPU time. For other benchmark problems with jobs between 50 and 100, the proposed algorithm, ADJ-Reduced improved the existing best known values within a practical time frame.