We analyse the interaction between a seller and customers in a shop on the fruits and vegetables wholesale market in Marseille using an unique data set. We find that customers’ bargaining activity is correlated with the kind and location of the business. To determine how the interactions between the seller and the customers influence prices, we compare the price each customer pays for a given g...

Nowadays most commercial e-shops do not offer any shop assistance or just in a very poor manner. But an e-customer expects guidance and advertising as he or she is used from traditional shops. In this paper we present an approach how personal shopping feeling and individual advertising can be integrated into a shop of the new economy. We show how customer behavior can be described in the prefer...

The general job-shop scheduling problem is known to be extremely hard. We describe a GA approach which produces reasonably good results very quickly on standard benchmark job-shop scheduling problems, better than previous eeorts using genetic algorithms for this task, and comparable to existing conventional search-based methods. The representation used is a variant of one known to work moderate...

This paper addresses the open shop scheduling problem. this problem, due to its complexity, is ranked in the class of NPhard problems. In this case, traditional approaches cannot reach to an optimal solution in a reasonable time. So heuristic algorithms such as simulated Annealing (SA), tabu search (TS) genetic algorithm, (GA), ant colony optimization (ACO) used to solve optimization problems s...

Mass-customization production (MCP) companies must fight with shop-floor uncertainty and complexity caused by wide variety of product components. The research is motivated by a typical MCP company that has experienced inefficient scheduling due to paper-based identification and manual data collection. This paper presents an RFID-enabled real-time manufacturing execution system (RT-MES). RFID de...

The Flexible Job Shop Scheduling Problem (FJSP) is one of the most general and difficult of all traditional scheduling problems. The Flexible Job Shop Problem (FJSP) is an extension of the classical job shop scheduling problem which allows an operation to be processed by any machine from a given set. The problem is to assign each operation to a machine and to order the operations on the machine...

Uncertainty plays a significant role in modeling and optimization of real world systems. Among uncertain approaches, fuzziness describes impreciseness while for ambiguity another definition is required. Vagueness is a probabilistic model of uncertainty being helpful to include ambiguity into modeling different processes especially in industrial systems. In this paper, a vague set based on dista...

This paper presents an agent-based service-oriented framework to address the challenges for integrating real time shop floor scheduling and control in a multi-workcell environment. The proposed framework enables shop floor to adapt to the changes in the environment dynamically. Shop floor scheduling and control can address dynamic changes either within a workcell, such as machine breakdowns, or...

This paper presents a new algorithm based on integrating Genetic Algorithms and Tabu Search methods to solve the Job Shop Scheduling problem. The idea of the proposed algorithm is derived from Genetic Algorithms. Most of the scheduling problems require either exponential time or space to generate an optimal answer. Job Shop scheduling (JSS) is the general scheduling problem and it is a NP-compl...

The job-shop scheduling problem has attracted many researchers’ attention in the past few decades, and many algorithms based on heuristic algorithms, genetic algorithms, and particle swarm optimization algorithms have been presented to solve it, respectively. Unfortunately, their results have not been satisfied at all yet. In this paper, a new hybrid swarm intelligence algorithm consists of par...