C Rajendran

In this paper, we develop branch-and-bound algorithms for objectives such as sum of weighted flowtime, weighted tardiness and weighted earliness of jobs, for an m- machine no-wait (continuous) flowshop. We believe that there has been no prior work on exact algorithms for this problem setup with a variety of objective functions. For the interest of space, we confine our discussion to a subset of certain combination of these objectives and the extension to other objective combinations is quite straight-forward. We explore the active nodes of a branch-and-bound tree by deriving an assignment-matrix based lower bound, that ensures one-to-one correspondence of a job with its due date and weight. This idea is based on our earlier paper on general m- machine permutation flowshop (Madhushini et al. in J Oper Res Soc 60(7):991–1004, 2009) and here we exploit the intricate features of a no-wait flowshop to develop efficient lower bounds. Finally, we conclude our paper with the numerical evaluation of our branch-and-bound algorithms.

Corporate Social Performances (CSP) has a determining role in the Environmental, Social, and Governance (ESG) scores of firms. Corporate Social Responsibility (CSR) strategy scores in the ESG ratings can provide a measure of the CSP concerts of firms. We observe in this research, the mean differences in the CSR strategy scores and the ESG scores of firms in select developed economies such as; US, UK, Japan, and Australia, representing different geographical regions globally. Thomson Reuters ESG scores based on ten major parameters and over 400 company level indicators are used to empirically evidence the study. The initial data of average performances on ESG indicators of 939 firms considered for a period of five years from 2014 to 2018 is analyzed. The results imply that the mean differences in the CSR strategy scores are not significant, considering the developed economies, deliberated in the study. Along with that, we observe a significant mean difference in the ESG scores of Australian firms considered for the study, in comparison with the firms from other developed economies. And the study confirm that the CSR strategy scores are significant predictors of ESG performance scores of firms in the developed economies considered for study.

The Economic Lot Scheduling Problem (ELSP) on a single facility (or machine) with the time-varying lot-sizes approach and with sequence- independent/sequence-dependent setup times of parts or products is studied in this paper. The objective is to minimise the long-run average inventory carrying cost and setup costs of products. While the frequency of production of a product is determined from an existing heuristic, we allow for possible changes in the heuristically computed frequencies of parts (or products) and hence attempt to reduce the total cost per cycle during the metaheuristic search process. Three metaheuristics, namely, a Genetic Algorithm (GA), a Simulated-annealing Algorithm (SA) and an Ant-Colony Algorithm (ACA) are proposed. A new crossover operator is designed and incorporated in the proposed GA. New perturbation schemes are incorporated in the proposed SA. In the proposed ACA, the initialisation and updating of pheromone intensity (or trails) are done subject to certain conditions presented in this work. The best-performing existing heuristic algorithm and the proposed algorithms for ELSP with sequence-independent setup times of products are evaluated by considering a couple of benchmark problems and by generating many problems with different number of products and comparing the solutions. In addition, we consider the case of sequence-dependent setup times and the associated setup costs. The performances of the existing algorithm and the proposed algorithms are evaluated by considering a proposed (computationally simple) lower bound on total cost per cycle with the consideration of sequence-dependent setup times and the associated setup costs of products. The computational performance analyses reveal the effectiveness of the proposed metaheuristics. © 2007 Inderscience Enterprises Ltd.

Purpose: The purpose of this paper is to provide strategic recommendations for Indian hotel administrators for improving sustainability practices: environment, economic and social with respect to the supply chain members by analyzing performance dimensions and the importance attached to them. Design/methodology/approach: Importance performance analysis is a tool to analyze the perception of top-level, middle-level and first-level managers in hotels. Questionnaire is developed to collect the hotel manager’s perceptions. The snowball sampling method is used for data collection. Findings: The paper introduces specific sustainability practices, namely, environment, economic and social factors, at the interface of the tourism supply chain (TSC). This will allow the hotels to identify the importance and performance of various sustainability practices to achieve a long-term competitive advantage. The present work finds that the responding hotel managers have given highest importance to the sustainability practices within the organization and the hotel manager’s perception of sustainability practices in the TSC will vary with respect to the supply chain members. Research limitations/implications: The effort has been made to capture specific sustainability practices across the supply chain. The paper reinstates the fact that sustainability practices are not firm specific and should be practiced at the supply chain interface. The data for the study were taken from focal organizations perspective which is the hotels. Practical implications: Results provide the hotel administrators to develop appropriate strategies to improve their practices and functions by analyzing their strengths and weakness regarding their tangible and intangible assets. The identified sustainability practice attributes can act as a benchmark and drive the hotel industry toward possible cost-saving conditions by prioritizing the allocation of the resources while taking care of overall performance. Social implications: Results will help the hotel administrators to identify the better sustainability practices which will reduce the negative effects and protect the Mother Nature. Originality/value: The study included hotels/resorts from tourism locations: hill station, backwaters and coastal areas, specifically in the Indian context.

The Fixed-Charge Transportation Problem (FCTP) is an extension of the classical transportation problem. It considers a fixed charge (or a fixed cost) and a transportation cost per unit transported associated with each route. The presence of the fixed cost in the objective function makes the problem difficult to solve, thereby requiring the use of heuristic methods. In this paper, simple heuristic algorithms are proposed, and their performances are compared with the existing best method by making use of benchmark problem instances. Copyright © 2009, Inderscience Publishers.

Purpose: The purpose of this paper is to provide strategic recommendations to supply chain managers of Indian manufacturing industries for a robust supply chain related to risk management by original equipment manufacturers (OEMs) and suppliers in manufacturing industries to ensure a robust supply chain risk management (SCRM). Design/methodology/approach: Importance-performance analysis (IPA) is utilized to identify and provide strategic recommendations to manufacturing industries for improving their supply chain performance by attaching due importance to risk constructs and appropriately choosing mitigation strategies. Findings: The investigation using the strategic action grids reveals that most of the means of risks are near the point of intersection of the grand means of the risk constructs and their impact on the supply chain, indicating that all the risks have the equal likelihood of occurrence. The mean importance of risk monitoring, risk avoidance (RA) and risk sharing surpass the mean performance for both OEMs and suppliers. Research limitations/implications: The study is executed with following limitations: the study assumes that the manufacturing industries across different sectors perceive similar risk. The sectors considered are automotive, heavy engineering, general engineering and home appliances. The Southern States of India are considered because of the dominant presence of many industries, especially automotive industries. However, it should be noted that these States form the manufacturing hubs where the lead organizations are functioning along with their major suppliers. Practical implications: By understanding the importance of SCRM dimensions and utilization of these dimensions, firms can mitigate the impact of risk on the supply chain. The detailed study of SCRM strategies highlights the importance attached to risk factors, mitigation strategies, and top management commitment. By the implementation of SCRM strategies, supply chain managers can improve the firm’s performance. Originality/value: The study involves empirically validated data on SCRM dimensions. The IPA is performed on the SCRM dimensions to investigate the importance attached to the factors of the dimensions and their performance.

Particle swarm optimisation (PSO) algorithms are applied in a variety of fields. A good quality solution for a problem depends on the PSO parameters chosen for the problem under study. In this paper, a continuous particle swarm optimisation algorithm is proposed to solve the unconstrained optimisation problems. This paper proposes a novel and simple variation of the PSO algorithm by introducing dynamic updating of velocity without any parameters, such as inertia weight and constriction coefficients that are commonly used in the traditional PSO algorithms. The proposed algorithm is applied to well-known benchmark functions which are commonly used to test the performance of numeric optimisation algorithms, and the results are compared with the existing PSO algorithms. It is found that the proposed algorithm gives superior results in terms of speed of convergence and the ability of finding the solutions of excellent quality. Copyright © 2012 Inderscience Enterprises Ltd.

Convoy movement problem (CMP) is an important optimisation problem, especially occurring in military logistics, which focuses on routing convoys concurrently in a network. The CMP is subject to constraints for preventing certain interactions between convoys such that the objectives related to travel times of them are minimised. We propose a Lagrangian relaxation (LR) approach to efficiently obtain a lower bound on the optimal solution. Our LR approach does not have integrality property, and hence the lower bound obtained is always tigher than the lower bound obtained using the LP relaxation. As CMP is an NP-complete problem, lower bounds are useful to evaluate the solutions obtained by a heuristic. From our computational experimentation, it is found that the proposed LR approach is superior to the existing LR approach.

We consider the flowshop scheduling problem with the twin-objective of minimizing makespan and total flowtime. We apply the Simulated Annealing (SA) technique to develop the proposed heuristic. Two new heuristics are proposed to provide the seed sequences for the SA heuristic. When compared with the existing heuristics, the proposed SA heuristic is found to perform much better. © 1994.

In traditional supply chain inventory management, orders used to be the major information that firms exchanged. Information sharing among firms within a supply chain has been a cornerstone of recent innovations in supply chain management. Lee et al. (2000) considered a two-level supply chain, consisting of a manufacturer and a retailer, with non-stationary AR(1) end demand and showed that the manufacturer benefits significantly when the retailer shares its demand information. In our work, we extend the study to quantify the value (i.e., benefit) of information sharing (in terms of demand variance reduction and inventory reduction) to a multi-stage serial supply chain with the number of stages greater than two. The lead time at every stage is positive and deterministic. Base stock levels at each installation are calculated under two scenarios-no information sharing and complete information sharing. The dependency of the benefit of information sharing on parameters like demand correlation and lead times is presented. It is seen that as the number of stages in a serial supply chain increases, the demand variance and hence the bullwhip effect increases; so is the case with an increase in the demand correlation. In addition, a comparative study of a supply chain with stages having respective lead times in decreasing order and a supply chain with stages having respective lead times in increasing order has also been carried out in order to relatively analyze the benefits of information sharing at different stages across these two supply chain settings. It is possibly for the first time in the literature that the benefit of information sharing has been studied and quantified (in terms of the reduction in the total demand variation and the reduction in inventory) in a multi-stage serial supply chain with more than three stages with positive and deterministic lead times.