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Most scheduling problems are complex combinatorial problems and very difficult to solve [Manage. is why, lots of methods focus on the optimization according to a single criterion (makespan, workloads of machines, waiting times, etc.). The combining of several criteria induces additional complexity and new problems. In this paper, we propose a Pareto(More)
Most complex scheduling problems are combinatorial problems and difficult to solve. That is why, several methods focus on the optimization according to a single criterion such as makespan, workloads of machines, waiting times, etc. In this paper, the Choquet integral is introduced as a general tool for dealing with multiple criteria decision making and used(More)
Most scheduling problems are highly complex combinatorial problems. However, stochastic methods such as genetic algorithm yield good solutions. In this paper, we present a controlled genetic algorithm (CGA) based on fuzzy logic and belief functions to solve job-shop scheduling problems. For better performance, we propose an efficient representational(More)
This paper deals with the single-vehicle Problem witch concerns people transportation [2]. Pickup and Delivery Problem with Time Windows (I-Another importaut part of these researches deals with the PDPTII'). In the 1-PDPTW a vehicle must serve a PDPTW with limited tramportation vehicle capacities like collection of transportation requests by taking loahfrom(More)
This paper presented a genetic algorithm (GA) to solve the container storage problem in the port. This problem is studied with different container types such as regular, open side, open top, tank, empty and refrigerated containers. The objective of this problem is to determine an optimal containers arrangement, which respects customers' delivery deadlines,(More)