Indian Institute of Management Ahmedabad

About: Indian Institute of Management Ahmedabad is a education organization based out in Ahmedabad, India. It is known for research contribution in the topics: Context (language use) & Emerging markets. The organization has 1828 authors who have published 4011 publications receiving 59269 citations. The organization is also known as: IIMA & IIM Ahmedabad.

A scatter search algorithm for the single row facility layout problem

Abstract: The single row facility layout problem (SRFLP) is the problem of arranging facilities with given lengths on a line, with the objective of minimizing the weighted sum of the distances between all pairs of facilities. The problem is NP-hard and research has focused on heuristics to solve large instances of the problem. In this paper we present a scatter search algorithm to solve large size SRFLP instances. Our computational experiments show that the scatter search algorithm is an algorithm of choice when solving large size SRFLP instances within limited time.

An efficient genetic algorithm for single row facility layout

Abstract: The single row facility layout is the NP-Hard problem of arranging facilities with given lengths on a line, so as to minimize the weighted sum of the distances between all pairs of facilities. Owing to its computational complexity, researchers have developed several heuristics to obtain good quality solutions. In this paper, we present a genetic algorithm called GENALGO to solve large single row facility layout problem instances. Our algorithm uses standard genetic operators and periodically improves the fitness of all individuals. Our computational experiments show that our genetic algorithm yields high quality solutions in spite of starting with an initial population that is randomly generated. Our algorithm improves the previously best known solutions for the 19 instances of 58 benchmark instances and is competitive for most of the remaining ones.

Low carbon urban transport scenarios for China and India: A comparative assessment

Abstract: This paper assesses comparable urban transport scenarios for China and India. The assessment methodology uses AIM/End-use model with a detailed characterization of technologies to analyze two scenarios for India and China till the year 2050. The first scenario assumes continuation and enhancement, in both countries, of policies under a typical business-as-usual dynamics, like constructing metros, implementing national fuel economy standards, promoting alternate fuel vehicles and implementing national air quality standards. The alternative, low carbon scenario assumes application, in both countries, of globally envisaged measures like fuel economy standards as well as imposition of carbon price derived from a global integrated assessment modeling exercise aiming to achieve global 2 °C temperature stabilization target. The modeling results for both countries show that decarbonizing transport sector shall need a wide array of measures including fuel economy, low carbon fuel mix including low carbon electricity supply. The comparison of China and India results provides important insights and lessons from their similarities and differences in the choice of urban transport options. India can benefit from China’s experiences as it lags China in urbanization and income. Modeling assessments show that both nations can contribute to, as well as benefit by aligning their transport plans with global climate stabilization regime.

Social Identity and Governance: The Behavioral Response to Female Leaders

Abstract: This paper uses data from artefactual field experiments and surveys conducted in 61 villages in India to examine whether men and women respond differently to women as leaders. We investigate the extent to which behavior towards female leaders is influenced by experience with women in leadership positions. We find evidence of significant male backlash against female leaders, which can be attributed to the transgression of social norms and in particular, a violation of male identity, when women are assigned to positions of leadership through gender based quotas. Increased exposure to female leaders reduces the extent of bias.