This work develops a multi-objective, two-stage stochastic, non-linear, and mixed-integer mathematical model for relief pre-positioning in disaster management. Improved imbalance and efficacy measures are incorporated into the model based on a new utility level of the delivered relief commodities. This model considers the usage possibility of a set of alternative routes for each of the applied transportation modes and consequently improves the network reliability. An integrated separable programming-augmented e-constraint approach is proposed to address the problem. The best Pareto-optimal solution is selected by PROMETHEE-II. The theoretical improvements of the presented approach are validated by experiments and a real case study.
There are arguably potential wage gains from exports in developing countries. Export markets bring about opportunities for firms and successful exporting firms translate some of the benefits of exports to workers via employment and wage premia. Using comparable data for 61 developing and low-income countries, we document the prevalence of the export wage premia worldwide. With an extensive litterature review, we identify four major drivers of the wage premia: exporting firms hire more skilled workers, utilize more sophisticated machines, buy higher quality material inputs and are more productive than non-exporting firms. Our empirical analysis confirms the worldwide prevalence of these mechanisms and, furthermore, establishes a strong link to the estimated wage premia.
We consider a complex recyclable waste collection problem that extends the class of vehicle routing problems with intermediate facilities by integrating a heterogeneous fixed fleet and a flexible assignment of destination depots. Several additional side constraints, such as a mandated break period contingent on tour start time, multiple vehicle capacities, and site dependencies are also included. This specific problem was inspired by a real-world application and does not appear in the literature. It is modeled as an MILP which is enhanced with several valid inequalities. Due to the rich nature of the problem, state-of-the-art solvers are only able to tackle instances of small to medium size. To solve realistic instances, we propose a multiple neighborhood search heuristic capable of systematically treating all problem features and general enough to respond to the varying characteristics of the case study regions for which it is intended. The results show that the heuristic achieves optimality on small instances, exhibits competitive performance in comparison to state-of-the-art solution methods for special cases of our problem, and leads to important savings in the state of practice. Moreover, it highlights and quantifies the savings from allowing a flexible depot assignment. The data from the state of practice comes from a company in the waste collection industry in Geneva, Switzerland.
Classical energy planning models assume that consumers are rational, which is obviously rarely the case. This paper proposes an original method to take into account the consumer's real behavior in an energy model. This new hybrid model combines technical methods from operations research with behavioral approaches from social sciences and couples a classical energy model with a Share of Choice model.
Generally, each member of a supply chain (SC) optimizes his own individual objective and accordingly, plans his activities (e.g. production operations, inventories) without considering a global perspective. The goal of this work is the development of a multiobjective optimization model for cooperative planning between different manufacturing plants belonging to the same SC. The model aims at minimizing simultaneously the total production cost and the average of inventory level for several items and over a multi-period horizon. To solve this problem, a non-dominated sorting elitist genetic algorithm (NSGA-II) is developed to derive the Pareto frontsolutions. Several tests are developed to show the performance of the solution method and the behavior of the cooperative planning model with respect to different demand patterns. The proposed model shows high performance in the tested cases with comparison to the literature.
Demand forecast is a critical determinant of order quantity under newsvendor problem (NVP) framework and warrants major revision in the event of changing circumstances or happening of some unforeseen events having potential to alter the demand. Retailers of single period products such as fashion apparels are required to pass their orders far ahead of selling seasons and apply preseason two-stage ordering procedure, where an initial order (first stage) is followed by a final confirmed order (second stage). The enterprise forecasting experts may get additional information related to the occurrence of some unforeseen events that may significantly impact the initial demand estimation. In this paper, the potential impact of such events is combined using a weight factor to obtain revised demand forecasts. In this context, this paper develops inventory models under NVP framework to determine the optimal order quantity and weight factor on the basis of revised forecasts. Considering the bidirectional changes in demand, we formulate a unique objective function that operates as a profit maximization function for the positive demand adjustment and turns into a cost minimization function for the negative demand adjustment. Models developed without constraints at first instance are extended subsequently by incorporating constraints of budget limits, storage space capacity and required service level. Near closed form expressions of decision variables for four demand distributions with multiplicative demand forms are presented. The results demonstrate economic benefits of using revised demand through models developed, negative impact of constraints, and role of demand distribution entropy in determining the order size and expected profit.
This paper investigates the notion of changes in ambiguity over loss probabilities in the smooth ambiguity model developed by Klibano, Marinacci and Mukerji (2005). Changes in ambiguity over loss probabilities are expressed through the specific concept of stochastic dominance of order n de ned by Ekern (1980). We characterize conditions on the function capturing attitudes towards ambiguity under which an individual always considers one situation to be more ambiguous than another in a model of two states of nature. We propose an intuitive interpretation of the properties of this function in terms of preferences for harms disaggregation over probabilities, also labelled ambiguity apportionment.
One of the fastest growing approaches to teaching and learning in the new digital paradigm is the use of Massive Open Online Courses (MOOCs). They are categorised either as cMOOCs following a connectivist approach, or as xMOOCs based on behaviourist principles. However, in xMOOC environments, forums may play a real connectivist role if they are functioning as a community. This paper builds on the criteria of Herring (2004) in order to determine the existence and dynamics of a community. Forum participants, in a connectivist approach, create knowledge together by requesting help, answering questions, discussing concepts and techniques, and suggesting applications and additional learning material. This research questions the existence of a clear distinction between cMOOCs and xMOOCs. It was also observed that gender roles in STEM classes are replicated online. Online teaching nowadays is no longer based on one-way processes but includes users in multi-way processes. These dynamics may be effective in ensuring a strong and well-functioning learning community.
Le capital humain et les politiques visant à sa création et à sa préservation prennent de plus en plus d’importance dans les sociétés industrialisées. Cet article propose un survol de la littérature économique récente dans ce domaine. Le défi majeur qui occupe aujourd’hui le marché du travail est l’accélération du progrès technique, qui s’accompagne d’effets différenciés suivant le niveau de qualification des travailleurs. Deux théories sont évoquées pour analyser ces effets. D’une part, le progrès technique est vu comme biaisé en faveur des travailleurs qualifiés et défavorable aux moins qualifiés. D’autre part, et suite au phénomène de polarisation du marché du travail récemment observé, on peut cependant penser que la technologie est surtout substituable aux emplois du milieu de l’échelle. De ces constatations découlent plusieurs recommandations de politiques économiques, la principale étant de donner aux travailleurs les moyens d’être flexibles et polyvalents, ce qui passe par une éducation relativement générale plutôt que trop spécifique et cantonnée à un secteur ou une profession.
