Research in metaheuristics for combinatorial optimization problems has lately experienced
a noteworthy shift towards the hybridization of metaheuristics with other techniques for …

Given n items and m knapsacks, the Generalized Assignment Problem (GAP) is to find the
optimum assignment of each item to exactly one knapsack, without exceeding the capacity …

The Industrial Internet technologies are anticipated to enable agile manufacturing processes
in response to the growing demand for personalised products/services with shorter …

Known as an effective heuristic for finding optimal or near-optimal solutions to difficult
optimization problems, a genetic algorithm (GA) is inherently parallel for exploiting high …

A cross docking facility is a type of warehouse in supply chain management that allows
orders to be prepared with or without going through the phase of storing products in the …

This paper presents algorithms based on differential evolution (DE) to solve the generalized
assignment problem (GAP) with the objective to minimize the assignment cost under the …

Difficult combinatorial optimization problems coming from practice are nowadays often
approached by hybrid metaheuristics that combine principles of classical metaheuristic …

Pork stands out as the most extensively produced and consumed meat globally. With
advancements in technology, genetics, and management, the structure of the pig supply …

Traditionally, Network Function Virtualization uses Service Function Chaining (SFC) to place
service functions and chain them with corresponding flows allocation. With the advent of …

The well-known generalized assignment problem has many real-world applications. The
assignment costs between agents and tasks affected by several factors could be unstable …